Pier scour depth prediction method based on combination of physical simulation and numerical simulation

Abstract

The invention relates to the technical research field of ocean engineering construction, in particular to a pier scour depth prediction method based on the combination of physical simulation and numerical simulation, which is based on the fact that a physical model test can accurately reflect local microcosmic interaction between sediment and water flow, and can better reflect actual physical rules in spatial distribution. The numerical simulation can more accurately reflect the nonlinear coupling change rule between the hydrodynamic force and the sediment action under the condition of different Reynolds numbers. Accordingly, numerical simulation and physical model tests are combined, the prediction accuracy of the local scouring form of the pier can be improved, the number of tests can be reduced, and the research cost can be reduced.

Description

Technical Field

[0001] The present invention relates to the research field of marine engineering construction technology, and in particular to a method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation. Background Art

[0002] At present, for the study of local scouring and silting of bridge piers, physical model experiments are the current normatively recognized technology. However, due to limited space, it is impossible to build a model of the on-site bridge piers in a 1:1 restoration. Experimental analysis can only be carried out by scaling the scale according to the similarity criterion. However, the scaling of local scouring and silting of bridge piers cannot simultaneously meet the geometric similarity, relative motion (velocity) scale similarity, and mechanical similarity. For example, when the bridge pier scale is scaled according to the geometric scale, the sediment cannot be scaled according to the scale. If the sediment size is scaled according to the scale, the mechanical properties will change greatly, which is inconsistent with the actual sediment hydrodynamic interaction. Therefore, in the model experiment, the sediment does not meet the geometric similarity and dynamic similarity. Although, in order to reflect the actual local scouring and silting law of bridge piers as much as possible, a large scale will be selected as much as possible, but due to the limitation of the test site, there is always a significant gap with the actual size.

[0003] In order to obtain the conversion relationship between the physical model test results and the actual size results, the existing method conducts physical model experiments of various scales, and extrapolates the results to 1:1 scale (i.e., actual size) according to the change rules of the results under different scales. However, the existing method requires the production of models of various scales, which has high mold making costs, and the greater the difference between the test site and the actual scale, the greater the error of the extrapolation. Another way is to directly use CFD numerical simulation, but bypassing the numerical simulation results of the physical model test, due to its insufficient simulation accuracy and poor intuitiveness, it has not yet been widely recognized in the industry.

[0004] Specifically, the prior art mainly includes the following methods: 1. Series model test method Sha Yuqing et al. proposed to eliminate the deviation of model test results by conducting a series of normal model experiments with different geometric scales and extending the test results to the prototype. Specific technical approaches include: a. Design and construct a series of normal models with different geometric scales.

[0005] b. Carry out local scouring test on bridge piers in each model and record key data such as scouring depth.

[0006] c. When the results of the series of model tests are extrapolated to the prototype scour depth, a linear relationship can be drawn in double logarithmic coordinates with the geometric scale λh as the horizontal axis and the model scour depth value Ym as the vertical axis to deduce the prototype scour depth.

[0007] Advantages: strict parameter control, single variable, easy to control.

[0008] Disadvantages: high cost, need to make multiple sets of models, and repeatedly dismantle the models. In particular, the geometric scale used for the water depth of the bridge pier is always different from the geometric scale of the test sediment. It is impossible to ensure the unity of the geometric scales of the two in the model, and it is impossible to strictly meet the starting similarity of the sediment and the similarity of the moving bed resistance.

[0009] Existing method 2: empirical formula method An empirical formula was obtained by performing dimensional analysis and parameter fitting on the results in the experimental flume and the observation results of the field prototype. The scour depth value of the actual scale prototype was calculated using the empirical formula using the physical model experimental results.

[0010] Advantages: Simple, prototype results can be converted using the empirical formulas of predecessors, and the cost is low.

[0011] Disadvantages: The empirical formula is based on previous experimental data and is limited by the experimental setting conditions. It may differ greatly from the actual working conditions. At this time, the accuracy of the empirical formula is unknown.

[0012] Existing method 3: Direct numerical simulation at actual scale Studies have shown that the maximum scour hole depth around bridge piers predicted by CFD methods is in good agreement with experimental results. However, some studies have pointed out that the steady-state solution CFD method may underestimate the scour depth in some cases, while the non-steady-state solution method may over-predict (Numerical Simulation of the Flow and Local Scour Process around Single and Complex Bridge Piers). Therefore, in practical applications, choosing a suitable CFD model and parameter settings is crucial to improving prediction accuracy.

[0013] Advantages: The CFD method can be used to reflect the actual three-dimensional flow field around the bridge pier. The experimental cost is relatively low and three-dimensional dynamic field analysis can be performed.

[0014] Disadvantages: The current technical level of numerical simulation using CFD method has the ability of engineering application. Due to the limitation of calculation amount and efficiency, it is still unable to directly consider the influence of sediment gradation. The ability of water flow to carry and transport sediment is generalized by critical starting shear stress and sediment transport rate. A large number of studies have shown that the local scour form of bridge piers simulated by numerical simulation is roughly close to the actual one, but there is still a large deviation from the actual one in terms of specific values, which can reach 7%~20%. In particular, the simulation accuracy of the wake vortex area downstream of the bridge pier is low.

[0015] In view of the defects existing in the above-mentioned prior art, the present application specifically proposes a method for predicting the scour depth of bridge piers based on the combination of physical simulation and numerical simulation to solve the above-mentioned technical problems. Summary of the invention

[0016] The present invention provides a method for predicting the scour depth of bridge piers based on a combination of physical simulation and numerical simulation. The basis of the present invention is that physical model tests can accurately reflect the local microscopic interaction between sediment and water flow, and can better reflect the actual physical laws in spatial distribution, while numerical simulation can more accurately reflect the nonlinear coupling change law between hydrodynamics and sediment action under different Reynolds numbers. Accordingly, combining numerical simulation and physical model tests can improve the prediction accuracy of the local scour morphology of bridge piers, reduce the number of tests, and reduce research costs.

[0017] The technical solution adopted by the present invention to solve the above technical problems is: a method for predicting the scour depth of bridge piers based on a combination of physical simulation and numerical simulation, comprising the following steps: Step 1: Make a scaled physical model according to the similarity criterion to conduct a physical model test of bridge pier scour and obtain the scour depth result; Step 2: Use the punching depth measurement results obtained in step 1 to adjust the parameters of the numerical calculation model and verify the model; Step 3: Design multiple physical model experimental schemes of different scales according to the physical model similarity criterion; Step 4: Use refined numerical calculations to simulate all physical model experimental schemes in step 3 and simulate the scouring of bridge piers at actual scale; Step 5: Compare the actual scale simulation results with the simulation results of all physical model experimental schemes to obtain the proportional relationship between the actual scale numerical simulation results and the numerical simulation results of the physical model experimental scheme.

[0018] Furthermore, in step 1, making a scaled physical model according to the similarity criterion to conduct a bridge pier scour physical model test includes: Step 1-1: Determine the scale of the model; Step 1-2: Conduct a pier scour model test.

[0019] Furthermore, the step 1-1 of determining the model ratio includes: Step 1-1-1: Determine the size of the bridge pier model and the model water depth according to the geometric similarity and relative water depth similarity criteria. Geometric similarity requires that the vertical size, horizontal size and water depth of the bridge pier model be reduced in equal proportions; Step 1-1-2: Measure the particle size distribution by laser particle size analyzer, and select natural sand with the same median particle size and distribution as the site as the model substrate; Step 1-1-3: Start the model sand flow rateV c test.

[0020] Furthermore, in step 1-1-3, the model sand starting flow rate is V c The test includes: a. Evenly arrange the natural sand in the sand pit in the middle of the water tank, and soak it in water for 24 hours after leveling to make it saturated. Before the test, take sand samples from the front, middle and back of the sand pit to measure the density, and slowly add water to the water tank to the target water level through a water pump, and use an underwater ultrasonic rangefinder to measure the initial bed elevation; b. Slowly increase the flow rate of the circulating water pump, monitor the flow rate changes in the water tank through ADV, observe the movement of sediment, and record the flow rate at the time when sediment movement begins on the bed surface, which is the starting flow rate of the model sand. V c ; c. Create flow according to the test conditions. The test time is 2 hours. After the test, measure the sediment elevation in the sand pit and the sediment mass in the sand collection box, and calculate the natural sand bed load sediment transport rate q. b , suspended sediment transport rate q s and washout rate e; d. Determine the average vertical velocity of the model based on the relative velocity similarity criterion.

[0021] Furthermore, the constraints that the model vertical average flow velocity needs to meet include that the model water flow should be in the square resistance area and the model water flow Reynolds number should be greater than 1000.

[0022] Furthermore, the step 1-2 of conducting the bridge pier scour model test includes: Step 1-2-1: Use a water flume to conduct a bridge pier scour test. Create a flow at the bottom of the left side of the water flume and discharge the flow at the bottom of the right side of the water flume. The model covers the entire width of the water flume. Arrange an acoustic Doppler velocimeter at a position three times the diameter of the pier upstream of the model pier to monitor the flow velocity. Use a combination of fixed-point terrain hourly measurement and timed section scanning around the pier to measure terrain scour changes. Step 1-2-2: Slowly add water to the water tank to the target water level through a water pump; Step 1-2-3: Obtain the target vertical average flow rate by controlling the water pump flow rate; Step 1-2-4: When the hourly measurement results of the fixed-point terrain around the pier model show that the change in scouring depth within 1 hour is less than the set threshold, it is considered that the maximum scouring depth has been reached. At this time, the test is terminated and the scouring depth results are recorded.

[0023] Furthermore, in step 2, the use of the punching depth measurement results obtained in step 1 to perform parameter adjustment and model verification on the numerical calculation model includes: Step 2-1: Establish a numerical calculation model; Step 2-2: Use experimental measurement data to calibrate the parameters of the numerical calculation model.

[0024] Furthermore, the establishment of the numerical calculation model in step 2-1 includes establishing a three-dimensional rectangular space including the bridge piers and the sediment bed, and calculating the water flow movement near the bridge piers and the sediment movement driven by the water flow by solving mathematical equations, thereby forming the terrain changes around the bridge piers, and the calculation is specifically performed using the following formula: a. The simulation of water flow motion uses the RANS mode to solve the Reynolds time-averaged equations to calculate the flow velocity, pressure and water level in three-dimensional space. The expression of the RANS equations is: (1) (2) in t is time; x i 、x j All are three-dimensional space coordinates; U i , U j are the time-averaged flow velocity; x i 、x j The subscript " i ”,“ j ” respectively represent the components of the variables in the three-dimensional space directions; p is water density; μ is hydrodynamic viscosity; μ t is the turbulent eddy viscosity coefficient of water flow. The two sides and the top of the rectangular calculation domain are set as symmetrical boundaries. The bottom of the calculation domain and the surface of the bridge pier adopt impermeable wall boundary conditions. The water surface uses the Level Set method to track the free surface. The inlet boundary uses the same flow rate as the physical model test to drive the water flow. The velocity at the inlet boundary is distributed in a logarithmic law vertically, and the outlet adopts the free outflow boundary condition. b. The calculation of sediment transport driven by water flow is divided into bed load sediment transport and suspended load sediment transport. The formula used for bed load sediment transport rate is: (3) (4) q b P is the sediment transport rate per unit width of bed load, which represents the sediment transport rate of bed load sediment in a vertical plane of unit width per unit time; EF is the probability of bed sediment starting; U b is the average sediment transport velocity; d is the particle diameter; μ d is the dynamic friction coefficient; θ is the Shields parameter, and the calculation formula is , where τ is the shear stress acting on the particle, P Sis the particle density, P is the density of water, g is the gravitational acceleration; θ c is the critical Shields parameter; The calculation formula for suspended sediment transport rate is: (5) where q s is the suspended sediment transport rate per unit width, representing the suspended sediment transport rate per unit time in a vertical plane with unit width; T is the sediment transport parameter, and its calculation formula is: , where τ c is the critical starting shear stress; Where D * is the dimensionless particle size, and its calculation formula is , where d is the particle diameter and s is equal to the particle density P S The ratio of v to water density P; v is the dynamic viscosity of water, reflecting the viscosity of the fluid; c. The evolution of the bottom topography is calculated by the sediment transport rate to obtain the change in bottom thickness. The calculation formula is: (6) Where h is the height of the bottom bed, n is the porosity, and A is the projected area on the horizontal plane. i Represents the number of the four sides, l i Represents the unit side length of the side, q b,i Representative i The single-width bed load transport rate of a surface.

[0025] Furthermore, the step 2-2 of calibrating the parameters of the numerical calculation model using the experimental measurement data includes: Step 2-2-1: Use the water depth, bridge pier and sediment particle size that are completely consistent with the physical model test, and the flow velocity, sediment density, and porosity that are completely consistent with the physical model test to perform numerical simulation, and output the flow velocity at 3 times the pier diameter upstream of the bridge pier model, the height of the bottom bed, and the maximum scour depth around the bridge pier and the maximum scour depth duration change, and compare them with the experimental measurement results; Step 2-2-2: Calibrate the bottom roughness height parameters of the numerical model to make the flow velocity and water depth obtained by numerical simulation consistent with the experimental measurement; Step 2-2-3: By calibrating the critical Shields parameter in the bed load transport rate formula and the critical starting shear stress parameter in the suspended load transport rate formula, the scour distribution and maximum scour depth of the bottom bed around the pier are consistent with experimental measurements.

[0026] The advantages of the present invention are: the present invention provides a method for predicting the scour depth of bridge piers based on the combination of physical simulation and numerical simulation, which has the following advantages: The basis of the present invention is that the physical model test can accurately reflect the local microscopic interaction between sediment and water flow, and can better reflect the actual physical laws in spatial distribution, while the numerical simulation can more accurately reflect the nonlinear coupling change law between hydrodynamics and sediment action under different Reynolds number conditions. Accordingly, combining numerical simulation and physical model tests can improve the prediction accuracy of the local scour morphology of bridge piers, and can also reduce the number of tests and reduce research costs; the present invention uses physical model experiments to adjust parameters and calibrate the numerical calculation model, and simulates the physical model experimental scheme with the help of calibrated numerical simulation technology to establish a deviation conversion relationship between the scale-scaled physical experimental results and the actual situation. Since the present invention can completely restore the actual scale 1:1 with the help of numerical simulation methods, the scale conversion relationship obtained is an interpolation when applied, which is different from the series model experiment method of prior art 1, which requires extrapolation and can greatly reduce the deviation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 Schematic diagram of calculation conditions and boundaries; Figure 2 This is a schematic diagram of the distribution of scour depth sampling points; Figure 3 The numerical diagram of the maximum scour depth at different scales obtained through numerical simulation and physical model test; Figure 4 It is a schematic diagram of the method flow of the present invention; DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] Embodiment 1: Figure 1 is the calculation condition and boundary diagram, Figure 2 This is a schematic diagram of the distribution of scour depth sampling points. Figure 3 This is a numerical diagram of the maximum scour depth at different scales obtained through numerical simulation and physical model tests. Figure 4 It is a schematic diagram of the method flow of the present invention, such as Figure 1 , Figure 2 , Figure 3 and Figure 4 As shown, the present invention proposes a method for predicting the scour depth of bridge piers based on a combination of physical simulation and numerical simulation, comprising the following steps: Step 1: Make a scaled physical model according to the similarity criterion to conduct a physical model test of bridge pier scour and obtain the scour depth result; Step 2: Use the punching depth measurement results obtained in step 1 to adjust the parameters of the numerical calculation model and verify the model; Step 3: Design 6 physical model experimental schemes with different scales according to the physical model similarity criterion. Specifically, refer to the method for determining the physical model scale in step 1 (refer to the geometric similarity and relative water depth similarity criteria to ensure that the model water flow is in the square resistance area and the water flow Reynolds number is greater than 1000), design 6 bridge pier models with different geometric scales (including the scale scheme determined in step 1, such as 1:40). In addition, the scheme with actual size on site needs to be considered as the C0 scheme. The examples of the schemes that need to be numerically simulated are as follows: Referring to the method for determining the scale of the physical model in step 1 (referring to the geometric similarity and relative water depth similarity criteria, ensuring that the model water flow is in the square resistance area and the water flow Reynolds number is greater than 1000), 6 bridge pier models with different geometric scales (including the scale scheme determined in step 1, such as 1:40) are designed. In addition, the scheme with actual size on site needs to be considered as the C0 scheme. The examples of the schemes that need to be numerically simulated are as follows:

[0031] Step 4: Use refined numerical calculation to simulate all the physical model experimental schemes in step 3, and simulate the scouring conditions of bridge piers at actual scales. Use the model and model parameters calibrated in step 2 to simulate the scouring of the above schemes, and obtain the sampling points around the bridge piers at different scales (such as Figure 2 The scour depth value and the maximum scour depth value are shown.

[0032] Step 5: Compare the actual scale simulation results with the simulation results of all physical model experimental schemes to obtain the proportional relationship between the actual scale numerical simulation results and the physical model experimental scheme numerical simulation results. Specifically, the conversion relationship between the scour depth values ​​of different scales to actual sizes at each sampling point around the bridge pier is obtained according to step 4, and the actual scale scour and silt distribution is obtained by converting the physical model test results; In step 1, making a scaled physical model according to the similarity criterion to conduct a bridge pier scour physical model test includes: Step 1-1: Determine the model scale, including: Step 1-1-1: Determine the size of the bridge pier model and the model water depth according to the geometric similarity and relative water depth similarity criteria. Geometric similarity requires that the vertical size, horizontal size and water depth of the bridge pier model be reduced in equal proportions; Step 1-1-2: Measure the particle size distribution by laser particle size analyzer, and select natural sand with the same median particle size and distribution as the site as the model substrate; Step 1-1-3: Start the model sand flow rate V c test.

[0033] Furthermore, in step 1-1-3, the model sand starting flow rate is V c The trials included; Step 1-2: Conduct a bridge pier scour model test, including: Step 1-2-1: Use a water flume to conduct a bridge pier scour test. Create a flow at the bottom of the left side of the water flume and discharge the flow at the bottom of the right side of the water flume. The model covers the entire width of the water flume. Arrange an acoustic Doppler velocimeter at a position three times the diameter of the bridge pier upstream of the model to monitor the flow velocity. Use a combination of fixed-point terrain hourly measurement and timed cross-section scanning around the bridge pier to measure terrain scour changes. Step 1-2-2: Slowly add water to the water tank to the target water level through a water pump; Step 1-2-3: Obtain the target vertical average flow rate by controlling the water pump flow rate; Step 1-2-4: When the hourly measurement results of the fixed-point terrain around the pier model show that the change in scouring depth within 1 hour is less than the set threshold (the threshold is 5% of the pier diameter or twice the ending particle size of the sediment, either one is sufficient), it is considered that the maximum scouring depth has been reached, and the test is terminated at this time, and the scouring depth results are recorded.

[0034] a. Evenly arrange the natural sand in the sand pit in the middle of the water tank, and soak it in water for 24 hours after leveling to make it saturated. Before the test, take sand samples from the front, middle and back of the sand pit to measure the density, and slowly add water to the water tank to the target water level through a water pump, and use an underwater ultrasonic rangefinder to measure the initial bed elevation; b. Slowly increase the flow rate of the circulating water pump, monitor the flow rate changes in the water tank through ADV, observe the movement of sediment, and record the flow rate at the time when a small amount of sediment moves on the bed surface, which is the starting flow rate of the model sand. V c ; c. Create flow according to the test conditions. The test time is 2 hours. After the test, measure the sediment elevation in the sand pit and the sediment mass in the sand collection box, and calculate the natural sand bed load sediment transport rate q. b , suspended sediment transport rate qs and washout rate e; d. According to the relative velocity similarity criterion (requiring the vertical average velocity U With starting flow rate V c Determine the average vertical velocity of the model by scaling it proportionally.

[0035] Furthermore, the constraints that the model vertical average flow velocity needs to meet include that the model water flow should be in the square resistance area and the model water flow Reynolds number should be greater than 1000.

[0036] Furthermore, in step 2, the use of the punching depth measurement results obtained in step 1 to perform parameter adjustment and model verification on the numerical calculation model includes: Step 2-1: Establish a numerical calculation model, including establishing a three-dimensional rectangular space containing bridge piers and sediment bottom beds, and calculating the water flow movement near the bridge piers and the sediment movement driven by the water flow by solving mathematical equations, thereby forming the terrain changes around the bridge piers. The specific calculation is based on the following formula: a. The simulation of water flow motion uses the RANS mode to solve the Reynolds time-averaged equations to calculate the flow velocity, pressure and water level in three-dimensional space. The expression of the RANS equations is: (1) (2) in t is time; x i 、x j All are three-dimensional space coordinates; U i , U j are the time-averaged flow velocities; i , x j The subscript " i ”,“ j " respectively represent the variables in the three-dimensional space direction ( i , j =1, 2, 3) p is water density; μ is hydrodynamic viscosity; μ t is the turbulent eddy viscosity coefficient of water flow. The two sides and the top of the rectangular calculation domain are set as symmetrical boundaries, the bottom of the calculation domain and the surface of the bridge pier adopt impermeable wall boundary conditions, and the water surface uses the Level Set method to track the free surface; the inflow boundary uses the same flow rate as the physical model test to drive the water flow, the velocity at the inlet boundary is distributed in a logarithmic law vertically, and the outlet adopts the free outflow boundary condition; b. The calculation of sediment transport driven by water flow is divided into bed load sediment transport and suspended load sediment transport. The formula used for bed load sediment transport rate is: (3) (4) q b P is the sediment transport rate per unit width of bed load, which represents the sediment transport rate of bed load sediment in a vertical plane of unit width per unit time; EF is the probability of bed sediment starting; U b is the average sediment transport velocity; d is the particle diameter; μ d is the dynamic friction coefficient; θ is the Shields parameter, and the calculation formula is ,in is the shear stress acting on the particle, p s is the particle density, p is the density of water, g is the gravitational acceleration; θ c is the critical Shields parameter; The calculation formula for suspended sediment transport rate is: (5) where q s is the suspended sediment transport rate per unit width, representing the suspended sediment transport rate per unit time in a vertical plane with unit width; T is the sediment transport parameter, and its calculation formula is: , where τ c is the critical starting shear stress; Where D * is the dimensionless particle size, and its calculation formula is , where d is the particle diameter and s is equal to the particle density P s The ratio of v to water density P; v is the dynamic viscosity of water, reflecting the viscosity of the fluid; c. The evolution of the bottom topography is calculated by the sediment transport rate to obtain the change in bottom thickness. The calculation formula is: (6) in h is the bottom bed height, n is the porosity, A is the projected area on the horizontal plane, i Represents the number of the four sides, l i Represents the unit side length of the side, q b,i Representative i The single-width bed load transport rate of a surface.

[0037] Step 2-2: Use experimental measurement data to calibrate the parameters of the numerical calculation model, specifically including: Step 2-2-1: Use the water depth, bridge pier and sediment particle size that are completely consistent with the physical model test, and the flow velocity, sediment density, and porosity that are completely consistent with the physical model test to perform numerical simulation, and output the flow velocity at 3 times the pier diameter upstream of the bridge pier model, the height of the bottom bed, and the maximum scour depth around the bridge pier and the maximum scour depth duration change, and compare them with the experimental measurement results; Step 2-2-2: By calibrating the bottom roughness height parameters of the numerical model, the flow velocity and water depth obtained by numerical simulation are made consistent with the experimental measurements, thereby ensuring the accuracy of the hydrodynamic simulation results of the flow around the bridge piers; Step 2-2-3: By calibrating the critical Shields parameter in the bed load transport rate formula and the critical starting shear stress parameter in the suspended load transport rate formula, the scour distribution and maximum scour depth of the bottom bed around the bridge piers are made consistent with experimental measurements, thereby ensuring the accuracy of the simulation of the sediment scour law around the bridge piers.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A bridge pier scour depth prediction method based on a combination of physical simulation and numerical simulation is characterized by: The following steps are involved: Step 1: Make a scaled physical model according to the similarity criterion to conduct a physical model test of bridge pier scour and obtain the scour depth result; Step 2: Use the punching depth measurement results obtained in step 1 to adjust the parameters of the numerical calculation model and verify the model; Step 3: Design multiple physical model experimental schemes of different scales according to the physical model similarity criterion; Step 4: Use refined numerical calculations to simulate all physical model experimental schemes in step 3 and simulate the scouring of bridge piers at actual scale; Step 5: Compare the actual scale simulation results with the simulation results of all physical model experimental schemes to obtain the proportional relationship between the actual scale numerical simulation results and the numerical simulation results of the physical model experimental scheme.

2. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 1 is characterized in that: In step 1, making a scaled physical model according to the similarity criterion to conduct a bridge pier scour physical model test includes: Step 1-1: Determine the scale of the model; Step 1-2: Conduct a pier scour model test.

3. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 2 is characterized in that: The step 1-1 of determining the modular scale comprises: Step 1-1-1: Determine the size of the bridge pier model and the model water depth according to the geometric similarity and relative water depth similarity criteria. Geometric similarity requires that the vertical size, horizontal size and water depth of the bridge pier model be reduced in equal proportions; Step 1-1-2: Measure the particle size distribution by laser particle size analyzer, and select natural sand with the same median particle size and distribution as the site as the model substrate; Step 1-1-3: Start the model sand flow rate V c test.

4. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 3 is characterized in that: In step 1-1-3, the model sand starting flow rate is V c The test includes: a. Evenly arrange the natural sand in the sand pit in the middle of the water tank, and soak it in water for 24 hours after leveling to make it saturated. Before the test, take sand samples from the front, middle and back of the sand pit to measure the density, and slowly add water to the water tank to the target water level through a water pump, and use an underwater ultrasonic rangefinder to measure the initial bed elevation; b. Slowly increase the flow rate of the circulating water pump, monitor the flow rate changes in the water tank through ADV, observe the movement of sediment, and record the flow rate at the time when sediment movement begins on the bed surface, which is the starting flow rate of the model sand. V c ; c. Create flow according to the test conditions. The test time is 2 hours. After the test, measure the sediment elevation in the sand pit and the sediment mass in the sand collection box, and calculate the natural sand bed load sediment transport rate q. b , suspended sediment transport rate q s and washout rate e; d. Determine the average vertical velocity of the model based on the relative velocity similarity criterion.

5. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 4 is characterized in that: The constraints that the model vertical average flow velocity needs to meet include that the model water flow should be in the square resistance area and the model water flow Reynolds number should be greater than 1000.

6. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 2 is characterized in that: The step 1-2 of conducting the bridge pier scour model test comprises: Step 1-2-1: Use a water flume to conduct a bridge pier scour test. Create a flow at the bottom of the left side of the water flume and discharge the flow at the bottom of the right side of the water flume. The model covers the entire width of the water flume. Arrange an acoustic Doppler velocimeter at a position three times the diameter of the pier upstream of the model pier to monitor the flow velocity. Use a combination of fixed-point terrain hourly measurement and timed section scanning around the pier to measure terrain scour changes. Step 1-2-2: Slowly add water to the water tank to the target water level through a water pump; Step 1-2-3: Obtain the target vertical average flow rate by controlling the water pump flow rate; Step 1-2-4: When the hourly measurement results of the fixed-point terrain around the pier model show that the change in scouring depth within 1 hour is less than the set threshold, it is considered that the maximum scouring depth has been reached. At this time, the test is terminated and the scouring depth results are recorded.

7. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 1 is characterized in that: In step 2, the use of the punching depth measurement results obtained in step 1 to adjust the parameters of the numerical calculation model and verify the model includes: Step 2-1: Establish a numerical calculation model; Step 2-2: Use experimental measurement data to calibrate the parameters of the numerical calculation model.

8. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 7 is characterized in that: The establishment of the numerical calculation model in step 2-1 includes establishing a three-dimensional rectangular space containing bridge piers and sediment bottom beds, and calculating the water flow movement near the bridge piers and the sediment movement driven by the water flow by solving mathematical equations, thereby forming the terrain changes around the bridge piers. The calculation is specifically performed using the following formula: a. The simulation of water flow motion uses the RANS mode to solve the Reynolds time-averaged equations to calculate the flow velocity, pressure and water level in three-dimensional space. The expression of the RANS equations is: （1） （2） in t is time; x i 、x j All are three-dimensional space coordinates; U i , U j are the time-averaged flow velocity; x i 、x j The subscript in " i ”," j ” respectively represent the components of the variables in the three-dimensional space directions; p is water density; μ is hydrodynamic viscosity; μ t is the turbulent eddy viscosity coefficient of water flow. The two sides and the top of the rectangular calculation domain are set as symmetrical boundaries. The bottom of the calculation domain and the surface of the bridge pier adopt impermeable wall boundary conditions. The water surface uses the Level Set method to track the free surface. The inlet boundary uses the same flow rate as the physical model test to drive the water flow. The velocity at the inlet boundary is distributed in a logarithmic law vertically, and the outlet adopts the free outflow boundary condition. b. The calculation of sediment transport driven by water flow is divided into bed load sediment transport and suspended load sediment transport. The formula used for bed load sediment transport rate is: （3） （4） q b P is the sediment transport rate per unit width of bed load, which represents the sediment transport rate of bed load sediment in a vertical plane of unit width per unit time; EF is the probability of bed sediment starting; U b is the average sediment transport velocity; d is the particle diameter; μ d is the dynamic friction coefficient; θ is the Shields parameter, and the calculation formula is , where τ is the shear stress acting on the particle, P S is the particle density, P is the density of water, g is the gravitational acceleration; θ c is the critical Shields parameter; The calculation formula for suspended sediment transport rate is: （5） where q s is the suspended sediment transport rate per unit width, representing the suspended sediment transport rate per unit time in a vertical plane with unit width; T is the sediment transport parameter, and its calculation formula is: , where τ c is the critical starting shear stress; Where D * is the dimensionless particle size, and its calculation formula is , where d is the particle diameter and s is equal to the particle density P S The ratio of v to water density P; v is the dynamic viscosity of water, reflecting the viscosity of the fluid; c. The evolution of the bottom topography is calculated by the sediment transport rate to obtain the change in bottom thickness. The calculation formula is: （6） Where h is the height of the bottom bed, n is the porosity, and A is the projected area on the horizontal plane. i Represents the number of the four sides, l i Represents the unit side length of the side, q b,i Representative i The single-width bed load transport rate of a surface.

9. The method for predicting bridge pier scour depth based on the combination of physical simulation and numerical simulation according to claim 7 is characterized in that: The step 2-2 of using experimental measurement data to calibrate the parameters of the numerical calculation model includes: Step 2-2-1: Use the water depth, bridge pier and sediment particle size that are completely consistent with the physical model test, and the flow velocity, sediment density, and porosity that are completely consistent with the physical model test to perform numerical simulation, and output the flow velocity at 3 times the pier diameter upstream of the bridge pier model, the height of the bottom bed, and the maximum scour depth around the bridge pier and the maximum scour depth duration change, and compare them with the experimental measurement results; Step 2-2-2: Calibrate the bottom roughness height parameters of the numerical model to make the flow velocity and water depth obtained by numerical simulation consistent with the experimental measurement; Step 2-2-3: By calibrating the critical Shields parameter in the bed load transport rate formula and the critical starting shear stress parameter in the suspended load transport rate formula, the scour distribution and maximum scour depth of the bottom bed around the pier are consistent with experimental measurements.

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