An intelligent size design method and construction method of a high-performance composite reinforcement layer

Abstract

The present invention discloses an intelligent size design method for a high-performance composite reinforcement layer and a construction method thereof, including obtaining damage data and basic parameters of a damaged beam, determining the degree of damage and the design strength of the reinforced beam according to the damage data, determining the value range of the non-uniformity coefficient and the equivalent section moment of inertia according to the design strength, determining the size design range of the composite reinforcement layer according to the value range of the equivalent section moment of inertia, constructing an intelligent size design model for the composite reinforcement layer, optimizing the intelligent size design model for the composite reinforcement layer according to an optimization objective function, and inputting the damage data and basic parameters of the damaged beam to be reinforced into the optimized intelligent size design model for the composite reinforcement layer to obtain the design size of the composite reinforcement layer. The present invention designs the composite reinforcement layer for the damaged beam by obtaining the damage data and basic parameters of the damaged beam, processing the damage data and calculating the size design range of the composite reinforcement layer.

Description

Technical Field

[0001] The invention relates to the field of dimension design, and in particular to an intelligent dimension design method for a high-performance composite reinforcement layer and a construction method thereof. Background Art

[0002] As the service life of buildings increases, more building beams suffer structural damage, and the need for structural reinforcement becomes more urgent. The use of high-performance concrete in structural reinforcement can solve many limitations of material properties and construction processes. Among them, the combination of engineering cement-based composites (ECC) and fiber-reinforced composites (FRP) has attracted much attention. Combining the high toughness, high ductility, crack resistance and earthquake resistance of ECC with the light weight and high strength of FRP can give full play to the reinforcement effect of the composite reinforcement layer, which is of great significance to the safety of building structures.

[0003] When using FRP-ECC composite layer for reinforcement, the rationality of the size design of the composite reinforcement layer directly affects the reinforcement effect, structural safety and reinforcement cost. However, the size design of the composite reinforcement layer mainly relies on manual experience, which has problems such as low efficiency, large deviation in reinforcement effect and few reference cases. In addition, the size design of the composite reinforcement layer is also related to the damage conditions such as cracks and deflections of the current beam body. The determination of the state of the damaged beam body is the key to size design. By adjusting the size design method of the composite reinforcement layer, effectively determining the structural state of the damaged beam, conducting finite element simulation tests to obtain more reference data, and combining machine learning for efficient data processing and prediction, an accurate, efficient and fast intelligent size design method and construction method of high-performance composite reinforcement layer are designed to overcome the shortcomings of the existing high-performance composite reinforcement layer size design, which can provide technical support for building reinforcement and escort building safety. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent size design method and a construction method of a high-performance composite reinforcement layer.

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

[0006] The present invention comprises the following steps:

[0007] Acquiring damage data and basic parameters of the damaged beam, determining the damage degree according to the damage data, and determining the design strength of the reinforced beam according to the damage degree;

[0008] Determine the range of values ​​of the non-uniform coefficient of the longitudinal tensile reinforcement of the reinforced beam according to the design strength, and calculate the range of values ​​of the equivalent section moment of inertia of the reinforced beam according to the range of values ​​of the non-uniform coefficient;

[0009] Determine the design range of the size of the composite reinforcement layer according to the value range of the equivalent section inertia moment;

[0010] Constructing a composite reinforcement layer intelligent size design model according to the composite reinforcement layer size design range and the damage degree;

[0011] The composite reinforcement layer intelligent size design model is optimized according to the optimization objective function, and the damage data and basic parameters of the damaged beam to be reinforced are input into the optimized composite reinforcement layer intelligent size design model to obtain the design size of the composite reinforcement layer.

[0012] Furthermore, the method for determining the design strength of the reinforced beam includes:

[0013] Obtain damage data and basic parameters of damaged beams;

[0014] The deflection of the damaged beam was measured, and the cracks of the damaged beam were counted using the box counting method. The damage degree of the damaged beam was determined based on the deflection and cracks of the damaged beam. The expression is:

[0015] ψ=0.5ψ1+0.5ψ2

[0016]

[0017]

[0018] Where ψ is the comprehensive damage degree, ψ1 is the damage degree of the damaged beam deflection, ψ2 is the damage degree of the damaged beam crack, M d,p is the initial yield strength corresponding to the damaged beam, M d,u is the ultimate yield strength corresponding to the damaged beam, l p is the initial yield deflection of the damaged beam, l u is the ultimate yield deflection of the damaged beam, l1 is the current measured deflection of the damaged beam, N crack is the number of main cracks, d i is the distance between the main cracks, W i1 , W i2 is the width of the two cracks corresponding to the spacing between the main cracks in the i-th section, L is the length of the damaged beam, W max is the maximum main crack width, N h is the number of box counting grids, r is the side length of the box counting grid;

[0019] The strength of the damaged beam and the design strength of the composite reinforcement layer are determined according to the comprehensive damage degree of the damaged beam. The design strength of the reinforced beam is determined by the strength of the damaged beam and the design strength of the composite reinforcement layer. The expression is:

[0020] M s =M d +M u

[0021]

[0022]

[0023] Among them, M s is the design strength of the reinforced beam, M d is the damaged beam strength, M u The composite reinforcement layer is designed to improve strength, h is the height of the damaged beam section, b is the width of the beam section, and h z =hf y A s / σ c b is the distance from the edge of the tension zone to the neutral axis, h2 is the thickness from the bottom of the composite reinforcement layer to the center of the steel bar, f y is the yield strength of steel bar, A s is the cross-sectional area of ​​the steel bar, σ c is the ultimate tensile stress of concrete.

[0024] Furthermore, the method for calculating the value range of the equivalent section inertia moment of the reinforced beam from the value range of the non-uniform coefficient includes:

[0025] According to the design strength of the reinforced beam, the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress considering the hysteresis strain are determined. The longitudinal tensile reinforcement strain non-uniformity coefficient between cracks is determined by the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress. The expression is:

[0026]

[0027]

[0028]

[0029] where ρ te is the longitudinal tensile reinforcement ratio of the effective tensile concrete cross-sectional area of ​​the reinforced beam, σ te is the stress of the longitudinal tensile reinforcement considering the hysteresis strain, δ is the strain non-uniformity coefficient of the longitudinal tensile reinforcement, is the mean of the sum of the equivalent reinforcement areas of the FRP grid and the ECC layer, a1 is the mean empirical coefficient obtained by fitting the mean of the test data, and A te =0.5bh is the effective area of ​​tensile concrete, η=0.87 is the internal force arm coefficient, h0 is the effective section height, is the mean value of the mesh elastic modulus for selection, is the average cross-sectional area of ​​the selected grid, h p is the thickness of the steel bar protective layer, h aim =0.5a2h is the thickness of the composite reinforcement layer used in calculation, a2∈[b1,b2] is the proportional coefficient of the composite reinforcement layer obtained by finite element simulation, is the hysteresis strain of the composite reinforcement layer under bending moment, ε c ′ is the concrete strain before reinforcement, x c ′ f is the distance between the point where the concrete force in the compression zone acts and the edge of the compression zone, tk is the standard value of concrete axial tensile strength;

[0030] The range of equivalent section inertia moment of the reinforced beam is determined according to the range of the non-uniform coefficient δ of the longitudinal tensile reinforcement strain between cracks. The expression is:

[0031]

[0032] Among them I y is the equivalent section moment of inertia of the reinforced beam, E s is the elastic modulus of the steel bar, α E is the elastic modulus of the steel bar E s The elastic modulus of concrete E c The ratio of ρ is the tensile reinforcement ratio of the damaged beam before damage.

[0033] Furthermore, the method for determining the design range of the size of the composite reinforcement layer according to the value range of the equivalent section inertia moment includes:

[0034] The range of ECC layer thickness is determined according to the range of equivalent section inertia moment, and the expression is:

[0035]

[0036] where h e is the ECC layer thickness, E e is the elastic modulus of the ECC layer;

[0037] According to the value range of ECC layer thickness, the corresponding FRP mesh thickness is determined by using the threshold judgment method. After the FRP mesh thickness is selected, the value range of the ECC layer thickness is rounded to an integer.

[0038] Furthermore, the method for constructing the intelligent size design model of the composite reinforcement layer includes:

[0039] An integer value within the range of ECC layer thickness and the corresponding FRP mesh thickness are taken as the simulation design size. A finite element model of the reinforced beam is constructed according to the simulation design size to perform finite element simulation to obtain a composite reinforcement layer strength simulation value. The composite reinforcement layer design size range, the damage degree of the damaged beam, the composite reinforcement layer design enhanced strength and the composite reinforcement layer strength simulation value are combined into a reinforced beam feature data set. The reinforced beam feature data set is divided into a training set and a test set.

[0040] Constructing a composite reinforcement layer intelligent size design model, wherein the composite reinforcement layer intelligent size design model includes a physical consistency term, a BP neural network and a target optimization algorithm;

[0041] The physical consistency term uses a physical model to calculate the actual strength range of the composite reinforcement layer according to the design size range of the composite reinforcement layer and the known material properties, and selects the design size whose actual strength of the composite reinforcement layer is greater than the strength threshold of the composite reinforcement layer to ensure the physical consistency requirements. The physical model expression is:

[0042]

[0043]

[0044] Among them, M ′ u is the actual strength of the composite reinforcement layer, σ e is the ultimate tensile stress of ECC material, σ y is the ultimate tensile stress of the FRP mesh, ζ f is the strength factor of the FRP mesh, ε fu is the ultimate strain of the FRP mesh;

[0045] The BP neural network is used to learn the complex nonlinear relationship between the design size of the composite reinforcement layer, the actual strength of the reinforcement layer, the simulated value of the reinforcement layer strength and the damage degree of the damaged beam, and predict the design size of the composite reinforcement layer; the ReLU activation function is used to increase the nonlinearity, and the mean square error loss function is used to predict the difference between the reinforcement layer strength and the actual reinforcement layer strength;

[0046] The target optimization algorithm selects the lowest reinforcement cost and the smallest error between the actual strength and the designed strength of the composite reinforcement layer as the optimization objectives, and uses the physical consistency term and size range as constraints. The hunter-prey optimization algorithm is used to optimize the hyperparameters of the intelligent size design model of the composite reinforcement layer according to the optimization objective function.

[0047] Furthermore, the method for optimizing the intelligent size design model of the composite reinforcement layer according to the optimization objective function includes:

[0048] Determine the optimization objective function, the expression is:

[0049]

[0050] Where F is the optimization objective function, w1 and w2 are the weights of the optimization objective function, β is the grid loss coefficient, and γ is the ECC mortar loss coefficient. The thickness is h f1 The price per unit area of ​​the grid, The thickness is h f2 The grid unit area price, h lis the exposed height of the beam, Price e is the unit volume cost of ECC mortar;

[0051] Initialize the population size N and dimension d, determine the maximum number of iterations T, calculate the individual fitness and update the optimal fitness, update the balance parameter C between exploration and development, and the adaptive parameter Z. The expression is:

[0052]

[0053]

[0054] in is a random vector in [0,1], R2 is a random number in [0,1], IDX is the index value that satisfies the condition P==0, and P is a random vector with a value of 0 or 1;

[0055] Update the position of the hunter or prey. When the random number R4 in [0,1] is less than 0.1, the hunter position is updated. The expression is:

[0056]

[0057] in is the next position of the hunter in the t+1th iteration, is the position of the hunter in the current t-th iteration, P pos To position the prey for escape, is the average position of all individuals in the population;

[0058] Each iteration considers that the number of prey decreases after the hunter kills the prey, and updates the prey position. The expression is:

[0059]

[0060]

[0061] Where P pos is the location where the prey escapes, which is the farthest from the average distance. At this moment, i is the number of prey after being hunted, which is k. best =round(C×N) prey population individuals, D is the Euclidean distance between all individuals and the average position;

[0062] When R4≥0.1, the prey moves towards P pos Escape, P pos Defined as the global optimal position T pos Update the prey position, the expression is:

[0063]

[0064] in is the next position of the prey in the t+1th iteration, is the position of the prey in the current t-th iteration;

[0065] Calculate the fitness of all individuals, update the optimal individual, and iterate continuously until the optimization objective function value is minimized or the maximum number of iterations is reached;

[0066] The damage data and basic parameters of the damaged beam to be reinforced are input into the optimized intelligent size design model of the composite reinforcement layer to obtain the design size of the composite reinforcement layer.

[0067] In a second aspect, a construction method of a high-performance composite reinforcement layer comprises the following steps:

[0068] Remove the plaster layer on the bottom and sides of the damaged beam until the concrete is exposed, use a steel brush to grind the bottom of the beam at 45° along the longitudinal direction until the aggregate on the bottom of the beam is exposed and there are clear scratches, and cut a U-shaped groove on the side of the beam with a length of 200mm and a depth of 10mm along the longitudinal direction of the beam and a height consistent with the exposed height of the beam body;

[0069] Cut the composite reinforcement layer FRP mesh and U-shaped hoop FRP mesh according to the size of the damaged beam, fix the composite reinforcement layer FRP mesh and U-shaped hoop FRP mesh with epoxy resin, apply a thin layer of epoxy resin on the FRP mesh and evenly sprinkle silica sand, drill holes at the bottom of the damaged beam and drive rivets 20mm in, mark the exposed part of the rivet at 0.5 and 1 times the thickness of the reinforcement layer, and insert the open washer at the 0.5 times mark;

[0070] Formwork is set up around the damaged beam, and ECC is sprayed in sections and layers at the bottom of the damaged beam to the mark of 0.5 times the rivet. The cut FRP mesh is clamped in the washer position to ensure that the FRP mesh is located in the middle of the composite reinforcement layer. ECC is sprayed in sections and layers to the mark of 1 times the rivet. The surface of the ECC at the bottom of the beam is smoothed and formwork is set up at the bottom. After curing to the designed strength, the formwork is removed to obtain the composite reinforcement layer.

[0071] ECC is sprayed in sections and layers in the U-shaped groove and FRP mesh is placed. When the spraying continues to the height of the beam side, the surface is smoothed and the side formwork is supported. After solidification to the designed strength, the formwork is removed to obtain the U-shaped hoop and continue maintenance.

[0072] Furthermore, the FRP grid is a bidirectional orthogonal grid material in warp and weft made of continuous basalt fiber roving as raw material, which is woven through a special process after being impregnated with glue. The mesh size of the composite reinforcement layer FRP grid is 50mm×50mm, and the thickness includes three specifications of 2mm, 3mm, and 5mm. The mesh size of the U-shaped hoop FRP grid is 30mm×30mm, and the thickness is 1mm.

[0073] Furthermore, the formula of the ECC includes: cement, quartz sand, water base, admixture and PVA; the water base includes water and water reducing agent; the admixture includes fly ash and silica fume; the mass ratio of the formula is cement: fine aggregate: water: water reducing agent: fly ash: silica fume = 500:500:335:7:360:25; the PVA is chopped fiber, added according to 2% slurry volume.

[0074] The beneficial effects of the present invention are:

[0075] The present invention is an intelligent size design method and construction method of a high-performance composite reinforcement layer. Compared with the prior art, the present invention has the following technical effects:

[0076] The present invention can improve the accuracy of dimensional design by determining the damage degree of a damaged beam, calculating the value range of the non-uniform coefficient, determining the value range of the equivalent section moment of inertia, determining the size design range of the composite reinforcement layer, building a model, and optimizing the model steps, thereby improving the efficiency and accuracy of the dimensional design of the high-performance composite reinforcement layer. The dimensional design can be made intelligent, which can greatly save resources, realize the dimensional design of the high-performance composite reinforcement layer for the damaged beam to be reinforced, and quickly perform high-precision dimensional design of the high-performance composite reinforcement layer for the reinforced damaged beam, thereby providing powerful technical support for the field of building reinforcement, and having important significance for realizing efficient repair of engineering structures and sustainable development of buildings.

[0077] The high-performance composite reinforcement layer provided by the present invention has the characteristics of good durability, high ductility, self-healing of micro cracks, light weight and high strength. The ECC is wrapped on the outside of the FRP grid and directly adhered to the concrete surface with ECC slurry as an adhesive, thereby avoiding the problems of easy aging of the FRP grid matrix glue and the epoxy resin glue used for pasting and fixing, poor UV resistance, etc., which helps to improve the service life of the FRP-ECC composite reinforcement layer; at the same time, the high-performance composite reinforcement layer construction method provided by the present invention arranges a U-shaped hoop on the side of the beam when fixing the FRP-ECC composite reinforcement layer, which helps to improve the structural integrity of the reinforced beam, improve the anti-peeling ability of the reinforcement layer and reduce the risk of stress concentration, thereby facilitating the development of structural reinforcement of damaged building structures. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 A flowchart of the steps of an intelligent size design method for a high-performance composite reinforcement layer of the present invention;

[0079] Figure 2 A schematic diagram of a reinforcement structure of a high-performance composite reinforcement layer construction method of the present invention;

[0080] Figure 3 It is a schematic diagram of a method for fixing a composite reinforcement layer and an internal grid of an auxiliary U-shaped hoop during construction of a high-performance composite reinforcement layer of the present invention;

[0081] Figure 4 A schematic cross-sectional view of a composite reinforcement layer during construction of a high-performance composite reinforcement layer according to the present invention;

[0082] Figure 5 It is a cross-sectional schematic diagram of an auxiliary U-shaped hoop during the construction of a high-performance composite reinforcement layer of the present invention;

[0083] In the figure: 1-damaged beam; 2-composite reinforcement layer; 3-U-shaped hoop; 4-1 composite reinforcement layer FRP mesh; 4-2 U-shaped hoop FRP mesh; 5-ECC; 6-rivet. DETAILED DESCRIPTION

[0084] The present invention is further described below by means of specific embodiments. The illustrative embodiments and descriptions of the present invention are used to explain the present invention but are not intended to limit the present invention.

[0085] The intelligent size design method and construction method of a high-performance composite reinforcement layer of the present invention include the following steps:

[0086] like Figure 1 As shown, in this embodiment, a smart size design method for a high-performance composite reinforcement layer includes:

[0087] Acquiring damage data and basic parameters of the damaged beam, determining the damage degree according to the damage data, and determining the design strength of the reinforced beam according to the damage degree;

[0088] Determine the range of values ​​of the non-uniform coefficient of the longitudinal tensile reinforcement of the reinforced beam according to the design strength, and calculate the range of values ​​of the equivalent section moment of inertia of the reinforced beam according to the range of values ​​of the non-uniform coefficient;

[0089] Determine the design range of the size of the composite reinforcement layer according to the value range of the equivalent section inertia moment;

[0090] Constructing a composite reinforcement layer intelligent size design model according to the composite reinforcement layer size design range and the damage degree;

[0091] The composite reinforcement layer intelligent size design model is optimized according to the optimization objective function, and the damage data and basic parameters of the damaged beam to be reinforced are input into the optimized composite reinforcement layer intelligent size design model to obtain the design size of the composite reinforcement layer.

[0092] In this embodiment, the method for determining the design strength of the reinforced beam includes:

[0093] Acquire damage data and basic parameters of the damaged beam; the damage data include damage beam deflection and damage beam crack data; the basic parameters include damage beam size, reinforcement ratio and material parameters;

[0094] According to the standard specifications, the damage data is used to calculate the original yield strength and ultimate strength of the damaged beam, and the deflection of the corresponding state is calculated according to the basic principles of concrete structure;

[0095] Directly measure the current deflection of the damaged beam, use the box counting method to segment the main cracks of the damaged beam, count the number of grid points, use the crack observation instrument to observe the cracks and record the crack width and spacing, and determine the damage degree of the damaged beam according to the deflection and crack conditions of the damaged beam. The expression is:

[0096] ψ=0.5ψ1+0.5ψ2

[0097]

[0098]

[0099] Where ψ is the comprehensive damage degree, ψ1 is the damage degree of the damaged beam deflection, ψ2 is the damage degree of the damaged beam crack, M d,p is the initial yield strength corresponding to the damaged beam, M d,u is the ultimate yield strength corresponding to the damaged beam, l p is the initial yield deflection of the damaged beam, l u is the ultimate yield deflection of the damaged beam, l1 is the current measured deflection of the damaged beam, N crack is the number of main cracks, d i is the distance between the main cracks, W i1 , W i2 is the width of the two cracks corresponding to the spacing between the main cracks in the i-th section, L is the length of the damaged beam, W max is the maximum main crack width, N h is the number of box counting grids, r is the side length of the box counting grid;

[0100] The strength of the damaged beam and the design strength of the composite reinforcement layer are determined according to the comprehensive damage degree of the damaged beam. The design strength of the reinforced beam is determined by the strength of the damaged beam and the design strength of the composite reinforcement layer. The expression is:

[0101] M s =M d +M u

[0102]

[0103]

[0104] Among them, M s is the design strength of the reinforced beam, M d is the damaged beam strength, M u The composite reinforcement layer is designed to improve strength, h is the height of the damaged beam section, b is the width of the beam section, and h z =hfy A s / σ c b is the distance from the edge of the tension zone to the neutral axis, h2 is the thickness from the bottom of the composite reinforcement layer to the center of the steel bar, f y is the yield strength of steel bar, A s is the cross-sectional area of ​​the steel bar, σ c is the ultimate tensile stress of concrete;

[0105] In the actual assessment, two damaged beams of a small two-lane highway bridge were structurally reinforced, and the basic parameters of the building were obtained: the single span size of the damaged beam was 2500*150*250mm, two HRB400 hot-rolled ribbed steel bars with a diameter of 10mm were arranged in the tension zone, corresponding to a yield strength / ultimate strength of 425 / 625MPa and an elastic modulus of 200GPa, and two HRB400 hot-rolled ribbed steel bars with a diameter of 8mm were arranged in the compression zone, corresponding to a yield strength / ultimate strength of 435 / 650MPa and an elastic modulus of 200GPa. C30 commercial concrete was used, corresponding to an elastic modulus of 35GPa and a compressive strength of 37.4MPa.

[0106] The yield strength / ultimate strength of the highway bridge before damage was calculated by the basic principle of reinforced concrete to be 80kN / 95kN, corresponding to a deflection of 5mm / 15mm. The deflection of the two damaged beams was measured to be 1.8mm / 3mm. The damage degrees of the damaged beam deflection were calculated to be 0.306 and 0.51 according to the formula. The damage degrees of the cracks of the damaged beams were calculated to be 0.478 and 0.655 by the box counting method, and the damage degrees of the two beams were 0.392 and 0.583 respectively.

[0107] The above formula determines that the design strength of the reinforced beam / the design strength of the composite reinforcement layer are 103.036kN / 45.303kN and 113.744kN / 74.129kN respectively.

[0108] In this embodiment, the method for calculating the value range of the equivalent section inertia moment of the reinforced beam from the value range of the non-uniformity coefficient includes:

[0109] According to the design strength of the reinforced beam, the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress considering the hysteresis strain are determined. The longitudinal tensile reinforcement strain non-uniformity coefficient between cracks is determined by the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress. The expression is:

[0110]

[0111]

[0112]

[0113] where ρte is the longitudinal tensile reinforcement ratio of the effective tensile concrete cross-sectional area of ​​the reinforced beam, σ te is the stress of the longitudinal tensile reinforcement considering the hysteresis strain, δ is the strain non-uniformity coefficient of the longitudinal tensile reinforcement, is the mean of the sum of the equivalent reinforcement areas of the FRP grid and the ECC layer, a1 is the mean empirical coefficient obtained by fitting the mean of the test data, and A te =0.5bh is the effective area of ​​tensile concrete, η=0.87 is the internal force arm coefficient, h0 is the effective section height, is the mean value of the mesh elastic modulus for selection, is the average cross-sectional area of ​​the selected grid, h p is the thickness of the steel bar protective layer, h aim =0.5a2h is the thickness of the composite reinforcement layer used in calculation, a2∈[b1,b2] is the proportional coefficient of the composite reinforcement layer obtained by finite element simulation, is the hysteresis strain of the composite reinforcement layer under bending moment, ε c ′ is the concrete strain before reinforcement, x c ′ f is the distance between the point where the concrete force in the compression zone acts and the edge of the compression zone, tk is the standard value of concrete axial tensile strength;

[0114] The range of equivalent section inertia moment of the reinforced beam is determined according to the range of the non-uniform coefficient δ of the longitudinal tensile reinforcement strain between cracks. The expression is:

[0115]

[0116] Among them I y is the equivalent section moment of inertia of the reinforced beam, E s is the elastic modulus of the steel bar, α E is the elastic modulus of the steel bar E s The elastic modulus of concrete E c The ratio of ρ is the tensile reinforcement ratio of the damaged beam before damage;

[0117] In the actual evaluation, a1 = 1.2 was obtained by fitting the mean of the test data, and the longitudinal tensile reinforcement ratio of the effective tensile concrete cross-sectional area of ​​the two reinforced beams was 1.3404%;

[0118] The average elastic modulus and cross-sectional area of ​​the available grids are 202.2 GPa and 6.04 mm 2The tensile reinforcement ratio of the damaged beam before damage is 0.8378%, and the effective section height is 225 mm. The composite reinforcement layer proportional coefficient a2∈[0.12,0.2] is obtained through the finite element simulation test of the reinforced beam. The longitudinal tensile reinforcement strain non-uniformity coefficients of the two reinforced beams are calculated to be in the range of 0.2886~0.2988 and 0.2726~0.2848, respectively, and the equivalent section inertia moment ranges from 0.000283522 to 0.000296916 m 4 、0.000302608~0.000321348m 4 .

[0119] In this embodiment, the method for determining the design range of the size of the composite reinforcement layer according to the value range of the equivalent section moment of inertia includes:

[0120] The range of ECC layer thickness is determined according to the range of equivalent section inertia moment, and the expression is:

[0121]

[0122] where h e is the ECC layer thickness, E e is the elastic modulus of the ECC layer;

[0123] According to the value range of ECC layer thickness, the threshold judgment method is used to determine the corresponding FRP mesh thickness. The specific judgment method is: when the ECC layer thickness is within 35mm, a 2mm thick FRP mesh is selected; when the ECC layer thickness is within 35-50mm, a 3mm thick mesh is selected; when the ECC layer thickness is above 50mm, a 5mm thick mesh is selected. After the FRP mesh thickness is selected, the ECC layer thickness can be slightly reduced, and the value range of the ECC layer thickness is rounded to an integer.

[0124] In the actual evaluation, the ECC elastic modulus is 25.6 GPa. The ECC layer thickness ranges of the two reinforced beams calculated above are 32-38 mm and 35-43 mm, respectively. The threshold judgment method is used to determine the corresponding FRP mesh thickness: when the ECC layer thickness of the first reinforced beam is 32-35 mm, the FRP mesh thickness is 2 mm, and when the ECC layer thickness is 35-38 mm, the FRP mesh thickness is 3 mm; the FRP mesh thickness of the second reinforced beam is 3 mm.

[0125] In this embodiment, the method for constructing the intelligent size design model of the composite reinforcement layer includes:

[0126] An integer value within the range of ECC layer thickness and the corresponding FRP mesh thickness are taken as the simulation design size. A finite element model of the reinforced beam is constructed according to the simulation design size to perform finite element simulation to obtain a composite reinforcement layer strength simulation value. The composite reinforcement layer design size range, the damage degree of the damaged beam, the composite reinforcement layer design enhanced strength and the composite reinforcement layer strength simulation value are combined into a reinforced beam feature data set. The reinforced beam feature data set is divided into a training set and a test set.

[0127] Constructing a composite reinforcement layer intelligent size design model, wherein the composite reinforcement layer intelligent size design model includes a physical consistency term, a BP neural network and a target optimization algorithm;

[0128] The physical consistency item uses a physical model to calculate the actual strength range of the composite reinforcement layer according to the design size range of the composite reinforcement layer and the known material properties, and selects the design size whose actual strength of the composite reinforcement layer is greater than the strength threshold of the composite reinforcement layer to ensure the physical consistency requirements. In actual reinforcement, the strength threshold of the composite reinforcement layer is 0.95M u , the physical model expression is:

[0129]

[0130]

[0131] Among them, M ′ u is the actual strength of the composite reinforcement layer, σ e is the ultimate tensile stress of ECC material, σ y is the ultimate tensile stress of the FRP mesh, ζ f is the strength factor of the FRP mesh, ε fu is the ultimate strain of the FRP mesh;

[0132] The BP neural network is used to learn the complex nonlinear relationship between the design size of the composite reinforcement layer, the actual strength of the reinforcement layer, the simulated value of the reinforcement layer strength and the damage degree of the damaged beam, and predict the design size of the composite reinforcement layer; the ReLU activation function is used to increase the nonlinearity, and the mean square error loss function is used to predict the difference between the reinforcement layer strength and the actual reinforcement layer strength;

[0133] The target optimization algorithm selects the lowest reinforcement cost and the smallest error between the actual strength and the designed strength of the composite reinforcement layer as the optimization objectives, and uses the physical consistency term and size range as constraints. The hunter-prey optimization algorithm is used to optimize the hyperparameters of the intelligent size design model of the composite reinforcement layer according to the optimization objective function.

[0134] In this embodiment, the method for optimizing the intelligent size design model of the composite reinforcement layer according to the optimization objective function includes:

[0135] Determine the optimization objective function, the expression is:

[0136]

[0137] Where F is the optimization objective function, w1 and w2 are the weights of the optimization objective function, β is the grid loss coefficient, and γ is the ECC mortar loss coefficient. The thickness is h f1 The price per unit area of ​​the grid, The thickness is h f2 The grid unit area price, h l is the exposed height of the beam, Price e is the unit volume cost of ECC mortar;

[0138] Initialize the population size N and dimension d, determine the maximum number of iterations T, calculate the individual fitness and update the optimal fitness, update the balance parameter C between exploration and development, and the adaptive parameter Z. The expression is:

[0139]

[0140]

[0141] in is a random vector in [0,1], R2 is a random number in [0,1], IDX is the index value that satisfies the condition P==0, and P is a random vector with a value of 0 or 1;

[0142] Update the position of the hunter or prey. When the random number R4 in [0,1] is less than 0.1, the hunter position is updated. The expression is:

[0143]

[0144] in is the next position of the hunter in the t+1th iteration, is the position of the hunter in the current t-th iteration, P pos To position the prey for escape, is the average position of all individuals in the population;

[0145] Each iteration considers that the number of prey decreases after the hunter kills the prey, and updates the prey position. The expression is:

[0146]

[0147]

[0148] Where P pos is the location where the prey escapes, which is the farthest from the average distance. At this moment, i is the number of prey after being hunted, which is k. best=round(C×N) prey population individuals, D is the Euclidean distance between all individuals and the average position;

[0149] When R4≥0.1, the prey moves towards P pos Escape, P pos Defined as the global optimal position T pos Update the prey position, the expression is:

[0150]

[0151] in is the next position of the prey in the t+1th iteration, is the position of the prey in the current t-th iteration;

[0152] Calculate the fitness of all individuals, update the optimal individual, and iterate continuously until the optimization objective function value is minimized or the maximum number of iterations is reached;

[0153] Input the damage data and basic parameters of the damaged beam to be reinforced into the optimized intelligent size design model of the composite reinforcement layer to obtain the design size of the composite reinforcement layer;

[0154] In the actual evaluation, the damage data and basic parameters of the damaged beam to be reinforced are input into the optimized intelligent size design model of the composite reinforcement layer to obtain the design dimensions of the composite reinforcement layer of the two reinforced beams, which are 35mm thick, 2mm thick, 40mm thick, and 3mm thick. At this time, the strength of the reinforced beam of the first beam is 110kN, and the actual strength of the composite reinforcement layer is 52.24kN, which is greater than 0.95M u =43.04kN; the strength of the second beam reinforcement is 126kN, and the actual strength of the composite reinforcement layer is 86.744kN, which is greater than 0.95M u =70.42kN.

[0155] like Figures 2 to 5 As shown, in this embodiment, a construction method of a high-performance composite reinforcement layer includes:

[0156] Remove the plaster layer on the bottom and sides of the damaged beam until the concrete is exposed, use a steel brush to grind the bottom of the beam at 45° along the longitudinal direction until the aggregate on the bottom of the beam is exposed and there are clear scratches, and cut a U-shaped groove on the side of the beam with a length of 200mm and a depth of 10mm along the longitudinal direction of the beam and a height consistent with the exposed height of the beam body;

[0157] Cut the composite reinforcement layer FRP mesh 4-1 and the U-shaped hoop FRP mesh 4-2 according to the size of the damaged beam, fix the composite reinforcement layer FRP mesh and the U-shaped hoop FRP mesh with epoxy resin, apply a thin layer of epoxy resin on the FRP mesh and evenly sprinkle silica sand, drill a hole at the bottom of the damaged beam and drive the rivet 6 into 20mm, mark the exposed part of the rivet 6 at 0.5 and 1 times the thickness of the reinforcement layer, and insert the open washer at the 0.5 times mark;

[0158] Formwork is set up around the damaged beam, and ECC5 is sprayed in sections and layers at the bottom of the damaged beam to the mark of 0.5 times the exposed part of rivet 6. The cut FRP mesh 4-1 is clamped in the washer position to ensure that the FRP mesh 4-1 is located in the middle of the composite reinforcement layer 2. ECC5 is sprayed in sections and layers to the mark of 1 times the exposed part of rivet 6. The surface of ECC5 at the bottom of the beam is smoothed and formwork is set up at the bottom. After curing to the designed strength, the formwork is removed to obtain the composite reinforcement layer 2;

[0159] ECC5 is sprayed in sections and layers in the U-shaped groove and FRP mesh 4-2 is placed. When spraying continues to the height of the beam side, the surface is smoothed and a formwork is supported on the side. After solidification to the designed strength, the formwork is removed to obtain the U-shaped hoop 3 and the maintenance is continued.

[0160] In this embodiment, the FRP grid is made of continuous basalt fiber roving, which is a bidirectional orthogonal grid material in warp and weft that is woven through a special process after being impregnated with glue. The mesh size of the reinforcement layer FRP grid 4-1 is 50mm×50mm, and the FRP grid specifications of the first and second reinforcement beams are 2mm and 3mm respectively. The mesh size of the U-shaped hoop FRP grid 4-2 is 30mm×30mm and the thickness is 1mm.

[0161] In this embodiment, the formula of the ECC includes: cement, quartz sand, water base, admixture and PVA; the water base includes water and water reducing agent; the admixture includes fly ash and silica fume; the mass ratio of the formula is cement: fine aggregate: water: water reducing agent: fly ash: silica fume = 500:500:335:7:360:25; the PVA is chopped fiber, added according to 2% slurry volume;

[0162] The specific preparation method of ECC slurry is:

[0163] Y1 Dry the dry material, pour the dry material into the mortar mixer, and dry mix for 2 to 3 minutes to obtain uniform dry material;

[0164] Add water and water reducing agent to Y2 and stir for 3-4 minutes to obtain a uniform slurry;

[0165] Y3: Sprinkle the PVA fibers evenly into the mortar and stir for 4 to 6 minutes to obtain a uniform ECC slurry without fiber agglomeration.

[0166] 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 principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent size design method for a high-performance composite reinforcement layer, characterized in that: The following steps are involved: S1. Acquire damage data and basic parameters of a damaged beam, determine the damage degree according to the damage data, and determine the design strength of the reinforced beam according to the damage degree; S2. Determine the range of values ​​of the non-uniform coefficient of the longitudinal tensile reinforcement of the reinforced beam according to the design strength, and calculate the range of values ​​of the equivalent section moment of inertia of the reinforced beam according to the range of values ​​of the non-uniform coefficient; S3. Determine the design range of the size of the composite reinforcement layer according to the value range of the equivalent section inertia moment; S4, constructing a composite reinforcement layer intelligent size design model according to the composite reinforcement layer size design range and the damage degree; S5, optimizing the intelligent size design model of the composite reinforcement layer according to the optimization objective function, inputting the damage data and basic parameters of the damaged beam to be reinforced into the optimized intelligent size design model of the composite reinforcement layer to obtain the design size of the composite reinforcement layer; The method for determining the design strength of the reinforced beam comprises: Obtain damage data and basic parameters of damaged beams; The deflection of the damaged beam was measured, and the cracks of the damaged beam were counted using the box counting method. The damage degree of the damaged beam was determined based on the deflection and cracks of the damaged beam. The expression is: ψ=0.5ψ1+0.5ψ2 Where ψ is the comprehensive damage degree, ψ1 is the damage degree of the damaged beam deflection, ψ2 is the damage degree of the damaged beam crack, M d,p is the initial yield strength corresponding to the damaged beam, M d,u is the ultimate yield strength corresponding to the damaged beam, l p is the initial yield deflection of the damaged beam, l u is the ultimate yield deflection of the damaged beam, l1 is the current measured deflection of the damaged beam, N crack is the number of main cracks, d i is the distance between the main cracks, W i1 , W i2 is the width of the two cracks corresponding to the spacing between the main cracks in the i-th section, L is the length of the damaged beam, W max is the maximum main crack width, N h is the number of box counting grids, r is the side length of the box counting grid; The strength of the damaged beam and the design strength of the composite reinforcement layer are determined according to the comprehensive damage degree of the damaged beam. The design strength of the reinforced beam is determined by the strength of the damaged beam and the design strength of the composite reinforcement layer. The expression is: M s =M d +M u Among them, M s is the design strength of the reinforced beam, M d is the damaged beam strength, M u The composite reinforcement layer is designed to improve strength, h is the height of the damaged beam section, b is the width of the beam section, and h z =hf y A s / σ c b is the distance from the edge of the tension zone to the neutral axis, h2 is the thickness from the bottom of the composite reinforcement layer to the center of the steel bar, f y is the yield strength of steel bar, A s is the cross-sectional area of ​​the steel bar, σ c is the ultimate tensile stress of concrete.

2. According to claim 1, a smart size design method for a high-performance composite reinforcement layer is characterized in that: The method for calculating the value range of the equivalent section inertia moment of the reinforced beam from the value range of the non-uniform coefficient includes: According to the design strength of the reinforced beam, the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress considering the hysteresis strain are determined. The longitudinal tensile reinforcement strain non-uniformity coefficient between cracks is determined by the longitudinal tensile reinforcement ratio and the range of longitudinal tensile reinforcement stress. The expression is: where ρ te is the longitudinal tensile reinforcement ratio of the effective tensile concrete cross-sectional area of ​​the reinforced beam, σ te is the stress of the longitudinal tensile reinforcement considering the hysteresis strain, δ is the strain non-uniformity coefficient of the longitudinal tensile reinforcement, is the mean of the sum of the equivalent reinforcement areas of the FRP grid and the ECC layer, A1 is the mean empirical coefficient obtained by fitting the mean of the test data, and A te =0.5bh is the effective area of ​​tensile concrete, η=0.87 is the internal force arm coefficient, h0 is the effective section height, is the mean value of the mesh elastic modulus for selection, is the average cross-sectional area of ​​the selected grid, h p is the thickness of the steel bar protective layer, 0.5a2h=h aim To calculate the thickness of the composite reinforcement layer, a2∈[b1,b2] is the proportional coefficient of the composite reinforcement layer obtained by finite element simulation. is the hysteresis strain of the composite reinforcement layer under bending moment, ε' c is the concrete strain before reinforcement, x' c f is the distance between the point where the concrete force in the compression zone acts and the edge of the compression zone, tk is the standard value of concrete axial tensile strength; The range of equivalent section inertia moment of the reinforced beam is determined according to the range of the non-uniform coefficient δ of the longitudinal tensile reinforcement strain between cracks. The expression is: Among them I y is the equivalent section moment of inertia of the reinforced beam, E s is the elastic modulus of the steel bar, α E is the elastic modulus of the steel bar E s The elastic modulus of concrete E c The ratio of ρ is the tensile reinforcement ratio of the damaged beam before damage.

3. According to claim 2, a smart size design method for a high-performance composite reinforcement layer is characterized in that: The method for determining the design range of the size of the composite reinforcement layer according to the value range of the equivalent section inertia moment includes: The value range of the ECC layer thickness is determined according to the value range of the equivalent section inertia moment, and the expression is: where h e is the ECC layer thickness, E e is the elastic modulus of the ECC layer; According to the value range of ECC layer thickness, the corresponding FRP mesh thickness is determined by using the threshold judgment method. After the FRP mesh thickness is selected, the value range of the ECC layer thickness is rounded to an integer.

4. According to claim 3, a smart size design method for a high-performance composite reinforcement layer is characterized in that: The method for constructing the intelligent size design model of the composite reinforcement layer comprises: An integer value within the range of ECC layer thickness and the corresponding FRP mesh thickness are taken as the simulation design size. A finite element model of the reinforced beam is constructed according to the simulation design size to perform finite element simulation to obtain the composite reinforcement layer strength simulation value. The composite reinforcement layer design size range, the damage degree of the damaged beam, the composite reinforcement layer design enhanced strength and the composite reinforcement layer strength simulation value are combined into a reinforced beam feature data set. The reinforced beam feature data set is divided into a training set and a test set. Constructing a composite reinforcement layer intelligent size design model, wherein the composite reinforcement layer intelligent size design model includes a physical consistency term, a BP neural network and a target optimization algorithm; The physical consistency term uses a physical model to calculate the actual strength range of the composite reinforcement layer according to the design size range of the composite reinforcement layer and the known material properties, and selects the design size whose actual strength of the composite reinforcement layer is greater than the strength threshold of the composite reinforcement layer to ensure the physical consistency requirements. The physical model expression is: Where M' u is the actual strength of the composite reinforcement layer, σ e is the ultimate tensile stress of ECC material, σ f is the ultimate tensile stress of the FRP mesh, ζ f is the strength factor of the FRP mesh, ε fu is the ultimate strain of the FRP mesh; The BP neural network is used to learn the complex nonlinear relationship between the design size of the composite reinforcement layer, the actual strength of the reinforcement layer, the simulated value of the reinforcement layer strength and the damage degree of the damaged beam, and predict the design size of the composite reinforcement layer; the ReLU activation function is used to increase the nonlinearity, and the mean square error loss function is used to predict the difference between the reinforcement layer strength and the actual reinforcement layer strength; The target optimization algorithm selects the lowest reinforcement cost and the smallest error between the actual strength and the designed strength of the composite reinforcement layer as the optimization objectives, and uses the physical consistency term and size range as constraints. The hunter-prey optimization algorithm is used to optimize the hyperparameters of the intelligent size design model of the composite reinforcement layer according to the optimization objective function.

5. According to claim 4, a smart size design method for a high-performance composite reinforcement layer is characterized in that: The method for optimizing the intelligent size design model of the composite reinforcement layer according to the optimization objective function includes: Determine the optimization objective function, the expression is: Where f is the optimization objective function, w1 and w2 are the optimization objective function weights, β is the grid loss coefficient, γ is the ECC mortar loss coefficient, The thickness is h f1 The price per unit area of ​​the grid, The thickness is h f2 The grid unit area price, h l is the exposed height of the beam, Price e is the unit volume cost of ECC mortar; Initialize the population size N and dimension d, determine the maximum number of iterations T, calculate the individual fitness and update the optimal fitness, update the balance parameter C between exploration and development, and the adaptive parameter Z. The expression is: in is a random vector in [0,1], R2 is a random number in [0,1], IDX is the index value that satisfies the condition P==0, and P is a random vector with a value of 0 or 1; Update the position of the hunter or prey. When the random number R4 in [0,1] is less than 0.1, the hunter position is updated. The expression is: in is the next position of the hunter in the t+1th iteration, is the position of the hunter in the current t-th iteration, P pos To position the prey for escape, is the average position of all individuals in the population, and N is the number of individuals in the population; Each iteration considers that the number of prey decreases after the hunter kills the prey, and updates the prey position. The expression is: Where P pos is the location where the prey escapes, which is the farthest from the average distance. At this moment, i is the number of prey after being hunted, which is k. best =round(C×N) prey population individuals, D is the Euclidean distance between all individuals and the average position; When R4≥0.1, the prey moves towards P pos Escape, P pos Defined as the global optimal position T pos Update the prey position, the expression is: in is the next position of the prey in the t+1th iteration, is the position of the prey in the current t-th iteration; Calculate the fitness of all individuals, update the optimal individual, and iterate continuously until the optimization objective function value is minimized or the maximum number of iterations is reached; The damage data and basic parameters of the damaged beam to be reinforced are input into the optimized intelligent size design model of the composite reinforcement layer to obtain the design size of the composite reinforcement layer.

6. A construction method for a high-performance composite reinforcement layer, for executing the method according to any one of claims 1 to 5, characterized in that: The following steps are involved: Z1. Remove the plaster layer on the bottom and sides of the damaged beam until the concrete is exposed. Use a steel brush to grind the bottom of the beam at 45° along the longitudinal direction until the aggregate on the bottom of the beam is exposed and there are clear scratches. Cut a U-shaped groove on the side of the beam with a length of 200mm and a depth of 10mm along the longitudinal direction of the beam and a height consistent with the exposed height of the beam body; Z2. Cut the composite reinforcement layer FRP mesh and U-shaped hoop FRP mesh according to the size of the damaged beam, fix the composite reinforcement layer FRP mesh and U-shaped hoop FRP mesh with epoxy resin, apply a thin layer of epoxy resin on the FRP mesh and evenly sprinkle silica sand, drill holes at the bottom of the damaged beam and drive rivets 20mm in, mark the exposed part of the rivet at 0.5 and 1 times the thickness of the reinforcement layer, and insert the open washer at the 0.5 times mark; Z3. Formwork is set up around the damaged beam, and ECC is sprayed in sections and layers at the bottom of the damaged beam to the mark of 0.5 times the rivet. The cut FRP grid is clamped in the gasket position to ensure that the FRP grid is located in the middle of the composite reinforcement layer. ECC is sprayed in sections and layers to the mark of 1 times the rivet. The ECC surface at the bottom of the beam is smoothed and formwork is set up at the bottom. After curing to the design strength, the formwork is removed to obtain the composite reinforcement layer. Z4. Spray ECC in sections and layers in the U-shaped groove and place FRP mesh. Continue spraying to the height of the beam side, smooth the surface and support the side formwork. After solidification to the designed strength, remove the formwork to obtain the U-shaped hoop and continue maintenance.

7. The construction method of a high-performance composite reinforcement layer according to claim 6, characterized in that: The mesh size of the composite reinforcement layer FRP grid is 50mm×50mm, and the thickness includes three specifications of 2mm, 3mm, and 5mm. The mesh size of the U-shaped hoop FRP grid is 30mm×30mm, and the thickness is 1mm.

8. The construction method of a high-performance composite reinforcement layer according to claim 6, characterized in that: The formula of the ECC includes: cement, quartz sand, water base, admixture and PVA; the water base includes water and water reducing agent; the admixture includes fly ash and silica fume; the mass ratio of the formula is cement: fine aggregate: water: water reducing agent: fly ash: silica fume = 500:500:335:7:360:25; the PVA is chopped fiber, which is added according to 2% slurry volume.

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