Reservoir dam body stress distribution intelligent optimization design method

Abstract

The application discloses a kind of reservoir dam body stress distribution intelligent optimization design method, it is related to water conservancy engineering technical field, including: the stress function of forming local block, the upper limit of stress of local block is obtained;Local block stress sharing coefficient is obtained;The maximum value of water pressure at local block is obtained, the upper limit of lateral stress of local block is obtained;Based on the upper limit of lateral stress, local block is divided into target local block and non-target local block;Based on target local block, at least two thickening regions are formed on the surface of reservoir dam body;The minimum thickening thickness of thickening region is obtained by analysis, and the optimization of to-be-optimized model is carried out.The stress function of forming local block, the stress sharing coefficient of local block, the maximum value of water pressure at local block and the thickening region and its minimum thickening thickness are formed, so that the structure optimization for stress can be completed under the condition of limited structure modification, and the optimization precision is high, and can meet the use demand.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering technology, specifically to an intelligent optimization design method for stress distribution in reservoir dams. Background Technology

[0002] Dam stress, in hydraulic engineering, refers to the internal stress generated in a dam under external forces. Its purpose is to understand the distribution and variation of compressive stress in the dam body, assess structural stability, provide a basis for safe operation and maintenance, and verify the accuracy of design calculations. Dam stress is mainly generated by deformation caused by water pressure. During the high-water season, rising water levels lead to increased water pressure, which may cause excessive stress in some parts of the dam, resulting in microcracks. This needs to be simulated in the early stages of dam modeling. However, current technology is insufficient in estimating the overall deformation of the dam under water pressure and the stress generated by this overall deformation, leading to insufficient accuracy in structural optimization based on stress. Summary of the Invention

[0003] To address the aforementioned technical problems, an intelligent optimization design method for stress distribution in reservoir dams is provided. This technical solution resolves the issues raised in the background section.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for intelligent optimization design of stress distribution in a reservoir dam body, comprising: A 3D model of the reservoir dam body is created to obtain the model to be optimized. The model to be optimized is then uniformly divided into at least two local blocks with equal height and width. The target material used in the local blocks is then obtained. Based on the target material, the stress function of a local block is formed, and the upper limit of the force on the local block is obtained through analysis. Obtain the maximum water level in the basin where the reservoir dam is located, perform stress analysis on the model to be optimized, and obtain the stress sharing coefficient of the local block; Based on the maximum water level and the stress sharing coefficient, the maximum water pressure at the local block is obtained through analysis, and based on the upper limit of the stress, the upper limit of the lateral stress at the local block is obtained through analysis. Based on the upper limit of lateral stress, the local blocks are divided into target local blocks and non-target local blocks; Based on the target local block, at least two thickened areas are formed on the surface of the reservoir dam; The minimum thickness of the thickened region is obtained through analysis, and the model to be optimized is optimized based on the minimum thickness.

[0005] Preferably, the stress function for forming a local block based on the target material includes the following steps: Based on the historical stress data of the existing reservoirs, the range of stress values ​​for local blocks is obtained; Divide the stress range into equal intervals to obtain at least two test points, set up a sample block, and make the sample block and the local block the same size and shape, and the sample block and the local block the same material. Place the back of the sample block against the wall, and set up force gauges on both sides of the sample block. Under the condition that the force on the front of the sample block is equal to the value of the test point, obtain the reading of the force gauges. Take the average of the readings of the two force gauges to obtain the measured reading. The stress function of the local block is obtained by pairing and fitting the test point values ​​with the measured readings.

[0006] Preferably, the analysis to obtain the upper limit of the force on the local block includes the following steps: Place the back of the sample block against the wall and apply pressure to the front of the sample block. When a crack appears in the sample block, the current applied pressure is taken as the upper limit of the force on the local block.

[0007] Preferably, the process of performing stress analysis on the model to be optimized to obtain the stress sharing coefficient of the local block includes the following steps: The center of the front surface of the local block is identified, and a tangent plane is drawn at the center of the front surface to obtain the feature plane. Draw the normal to the feature plane at the center of the front surface to obtain the feature line. Take the number of all local blocks that the feature line passes through as the feature value of the local block. The reciprocal of the eigenvalues ​​of the local block is used as the force-sharing coefficient of the local block.

[0008] Preferably, the step of analyzing and obtaining the maximum water pressure at a local block based on the maximum water level height and the stress sharing coefficient includes the following steps: The front surface of the local block is evenly divided into at least two local surfaces. The center of the local surface is identified. The difference between the maximum water level height and the height of the center of the local surface is used to obtain the liquid level difference of the local surface. The pressure on the local surface is calculated using the water pressure formula. The projection of the local surface onto the characteristic plane is taken as the target surface. The pressure of the local surface is multiplied by the area of ​​the corresponding target surface to obtain the pressure value of the local surface. The pressure values ​​of at least two local surfaces are superimposed to obtain the total pressure at the local block. The total pressure at the local block is multiplied by the force sharing coefficient to obtain the maximum water pressure at the local block. The water pressure formula is as follows: , Where P is the local pressure, p is the density of water, g is the acceleration due to gravity, and h is the liquid level difference at the local surface.

[0009] Preferably, the step of analyzing and obtaining the upper limit of lateral stress in a local block based on the upper limit of force includes the following steps: The distance between the center of the front surface and the center of the rear surface of the local block is taken as the thickness of the local block. The upper limit of the force is divided by the thickness of the local block and the area of ​​the front surface of the local block in turn to obtain the reference pressure. The upper limit of the lateral stress of the local block is obtained by multiplying the reference pressure by the width of the local block and the area of ​​the left surface of the local block.

[0010] Preferably, the step of dividing the local block into target local blocks and non-target local blocks based on the upper limit of lateral stress includes the following steps: Randomly select one of at least two local blocks as the feature local block. The local block set is initially empty. Fill the local block set with the feature local block. Add elements to the local block set by adding all local blocks that are adjacent to one of the local blocks in the local block set on the left or right until no more elements are added to the local block set. When the feature local block traverses all local blocks, at least two local block sets are formed; Substituting the maximum water pressure of the local block into the stress function of the local block, we obtain the estimated lateral stress of the local block. The estimated lateral stress values ​​of the local blocks in the local block set are superimposed to obtain the judgment value of the local block set; If the upper limit of the lateral stress of a local block in the local block set is less than the judgment value of the local block set, then the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block.

[0011] Preferably, forming at least two thickened areas on the surface of the reservoir dam based on the target local block includes the following steps: The surface with the higher water level on the front and rear surfaces of the reservoir dam is used as the reference surface; The intersection of the feature line of the target local block and the reference surface is used as the reference point. A thickened region is formed on the reference surface, so that the thickened region is consistent with the front surface of the target local block, and the center of the thickened region coincides with the reference point.

[0012] Preferably, the analysis to obtain the minimum thickening thickness of the thickened region includes the following steps: Based on historical construction data, the minimum variation value of the thickness is obtained, and the initial value of the thickness of the thickened area is equal to the minimum variation value. Step 1: Update the stress sharing coefficient of the local block. If the feature line of the local block passes through the thickened area, divide the thickness of the thickened area by the thickness of the local block to obtain the added value. Add the added value to the feature value of the local block to obtain the updated feature value of the local block. Use the reciprocal of the updated feature value of the local block as the updated stress sharing coefficient of the local block. Otherwise, the updated stress sharing coefficient of the local block is equal to the stress sharing coefficient of the local block. Step 2: Multiply the stress sharing coefficient of the local block by the total pressure at the local block to obtain the maximum value of the renewal water pressure at the local block. Substitute the maximum value of the renewal water pressure of the local block into the stress function of the local block to obtain the estimated value of the renewal lateral stress of the local block. Step 3: Superimpose the updated lateral stress estimates of the local blocks in the local block set to obtain the updated judgment value of the local block set; If the upper limit of the lateral stress of a local block in a local block set is less than the update judgment value of the local block set, the thickness of the thickened region is changed and updated. Each change and update increases the thickness of the thickened region by the minimum change value. After the change and update, steps one to three are repeated until there is no local block in a local block set whose upper limit of the lateral stress is less than the update judgment value of the local block set. The current thickness of the thickened region is taken as the minimum thickness of the thickened region.

[0013] Preferably, the optimization of the model to be optimized based on the minimum thickness includes the following steps: The thickened area is rotated to a horizontal position and designated as the feature area. The column formed by vertically moving the feature area by a distance equal to twice the minimum thickness of the thickened area is designated as the feature body. The center of the top surface of the feature body is taken as the first feature point, and the center of the bottom surface of the feature body is taken as the second feature point; The line connecting the first feature point and the second feature point is used as the baseline. Sampling points are obtained on the baseline such that the maximum value of the sampling point to the bottom edge of the feature body is equal to the distance from the sampling point to the first feature point. A feature sphere is formed with the sampling point as the center and the distance from the sampling point to the first feature point as the radius. The part where the feature sphere and the feature body overlap is taken as the thickened part, and the surface where the thickened part overlaps with the bottom surface of the feature body is taken as the bottom surface of the thickened part. Move the bottom surface of the thickened part to cover the corresponding thickened area, and merge the moved two thickened parts with the model to be optimized to complete the optimization.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By generating the stress function of local blocks, obtaining the stress sharing coefficient of local blocks, obtaining the maximum water pressure at local blocks, and forming thickened areas and their minimum thickening thickness, it is possible to estimate the transverse stress generated by the dam body under water pressure under the maximum water level during the high-water season, and to combine the resultant force generated by the stress. This allows for the analysis of target local blocks with stress bearing defects by combining the hardness of various locations of the dam. Then, based on the location of the target local blocks, targeted thickening can be carried out at the target local blocks. Thus, under limited structural modification conditions, structural optimization for stress can be completed with high optimization accuracy, meeting the usage requirements. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating an intelligent optimization design method for stress distribution in a reservoir dam body according to the present invention. Figure 2 This is a flowchart illustrating the stress function of forming a local block based on the target material according to the present invention. Figure 3 This is a schematic diagram of the process of performing stress analysis on the model to be optimized and obtaining the stress sharing coefficient of the local block according to the present invention. Figure 4 This is a schematic diagram of the process of analyzing and obtaining the maximum water pressure at a local block based on the maximum water level height and the stress sharing coefficient of the present invention. Figure 5 This is a schematic diagram illustrating the process of analyzing and obtaining the upper limit of lateral stress of a local block based on the upper limit of force according to the present invention. Figure 6 This is a schematic diagram illustrating the process of dividing a local block into a target local block and a non-target local block based on the upper limit of lateral stress according to the present invention. Figure 7 This is a schematic diagram illustrating the process of forming at least two thickened regions on the surface of a reservoir dam based on a target local block, according to the present invention. Figure 8 This is a schematic diagram illustrating the process of obtaining the minimum thickening thickness of the thickened region in the analysis of this invention; Figure 9 This is a schematic diagram of the process of optimizing the model to be optimized based on the minimum thickness of the present invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, a smart optimization design method for stress distribution in a reservoir dam body includes: A 3D model of the reservoir dam body is created to obtain the model to be optimized. The model to be optimized is then uniformly divided into at least two local blocks with equal height and width. The target material used in the local blocks is then obtained. Based on the target material, the stress function of a local block is formed, and the upper limit of the force on the local block is obtained through analysis. Obtain the maximum water level in the basin where the reservoir dam is located, perform stress analysis on the model to be optimized, and obtain the stress sharing coefficient of the local block; Based on the maximum water level and the stress sharing coefficient, the maximum water pressure at the local block is obtained through analysis, and based on the upper limit of the stress, the upper limit of the lateral stress at the local block is obtained through analysis. Based on the upper limit of lateral stress, the local blocks are divided into target local blocks and non-target local blocks; Based on the target local block, at least two thickened areas are formed on the surface of the reservoir dam; The minimum thickness of the thickened region is obtained through analysis, and the model to be optimized is optimized based on the minimum thickness.

[0018] When the model to be optimized is uniformly divided into at least two local blocks, the model to be optimized may be a curved dam or a non-curved dam. A non-curved dam is a straight dam, that is, a horizontal straight line set in the river channel, while a curved dam is similar to the Hoover Dam, which is a local part of the surface of a sphere. This is to save engineering materials. For a non-curved dam, the local block is square, but for a curved dam, the local block is arched, which is consistent with the curvature of the curved dam. Therefore, the front and back surfaces are the same curved surface, which will be used in subsequent processing. It is easy to know that the stress caused by deformation due to water pressure is most severe when the water level is highest. Therefore, we only need to analyze the stress at the maximum water level in the basin where the reservoir dam is located. If the optimized stress can meet the maximum water level, it can also meet the stress at other water levels. The optimization of this scheme mainly consists of two steps. First, the location of stress defects, i.e., the target local block, is identified. Second, the target local block is thickened. Since the direction of water pressure can be approximated as the direction along the feature line of the target local block, the thickening location is the intersection of the feature line of the target local block and the dam surface. Due to the large difference in water level between the front and rear sides of the dam, only the intersection on the side with the higher water level is considered, and the thickening is carried out at this location. The reason why thickening can optimize stress is as follows: the thicker the dam, the greater the pressure it can withstand, because the pressure is evenly distributed along the pressure direction. Therefore, when the dam is thickened, the pressure distributed by the local block along the feature line at the thickened location is reduced. As a result, the lateral deformation is smaller, and the compressive force generated by the deformation is smaller, thus reducing the overall resultant stress within the bearing capacity of the local block, thereby achieving optimization. For this purpose, it is only necessary to determine the thickness of the thickening, which will be analyzed in detail later. Here, the feature line is the normal line of the feature plane drawn at the center of the front surface of the target local block. When considering stress, only the stress caused by deformation in the left-right direction is considered. For the front-back and up-down directions, since the dam body is not restricted in these two directions, there is space for it to extend in these two directions when it deforms. Therefore, there will not be strong stress generated. However, the left-right direction of the dam body is restricted by the riverbanks on both sides. Therefore, there is no space for the dam body to extend in this direction, and its deformation will generate a stronger stress effect. Therefore, this is the main direction of stress generation. As long as the optimized structure can meet the stress requirements in this direction, it can also meet the stress generated in other directions. The water level and the height of the local blocks are both referenced to sea level.

[0019] Reference Figure 2 As shown, based on the target material, the stress function for forming a local block includes the following steps: Based on the historical stress data of the existing reservoirs, the range of stress values ​​for local blocks is obtained; Divide the stress range into equal intervals to obtain at least two test points, set up a sample block, and make the sample block and the local block the same size and shape, and the sample block and the local block the same material. Place the back of the sample block against the wall, and set up force gauges on both sides of the sample block. Under the condition that the force on the front of the sample block is equal to the value of the test point, obtain the reading of the force gauges. Take the average of the readings of the two force gauges to obtain the measured reading. The stress function of the local block is obtained by pairing and fitting the test point values ​​with the measured readings.

[0020] The stress is mainly generated by the water pressure squeezing the local block, causing the local block to deform laterally. The local block is connected to the adjacent local block, but since there is no space for extension, the deformation causes a squeezing force on the adjacent local block. The stress function is the function that measures the relationship between the two. However, since the materials used for local blocks in different locations may be different, different local blocks may use different stress functions. During testing, since the local block does not have a solid body, it is necessary to form a solid body consistent with the local block, i.e., a sample block.

[0021] The analysis to determine the upper limit of the force on a local block includes the following steps: Place the back of the sample block against the wall and apply pressure to the front of the sample block. When a crack appears in the sample block, the current applied pressure is taken as the upper limit of the force on the local block.

[0022] The cracks are minute and may be inside the sample block, therefore, they need to be tested using ultrasonic imaging.

[0023] Reference Figure 3 As shown, the stress analysis of the model to be optimized to obtain the stress sharing coefficient of the local blocks includes the following steps: The center of the front surface of the local block is identified, and a tangent plane is drawn at the center of the front surface to obtain the feature plane. Draw the normal to the feature plane at the center of the front surface to obtain the feature line. Take the number of all local blocks that the feature line passes through as the feature value of the local block. The reciprocal of the eigenvalues ​​of the local block is used as the force-sharing coefficient of the local block.

[0024] The force experienced by all local blocks through which the characteristic line passes is water pressure in the same direction. Therefore, when subjected to pressure, the pressure will be evenly distributed to these local blocks. Thus, the proportion of the pressure borne by each local block to the water pressure in that direction is equal to the reciprocal of the characteristic value. Therefore, it is used as the force sharing coefficient of the local block.

[0025] Reference Figure 4 As shown, based on the maximum water level and the stress sharing coefficient, the analysis to obtain the maximum water pressure at a local block includes the following steps: The front surface of the local block is evenly divided into at least two local surfaces. The center of the local surface is identified. The difference between the maximum water level height and the height of the center of the local surface is used to obtain the liquid level difference of the local surface. The pressure on the local surface is calculated using the water pressure formula. The projection of the local surface onto the characteristic plane is taken as the target surface. The pressure of the local surface is multiplied by the area of ​​the corresponding target surface to obtain the pressure value of the local surface. The pressure values ​​of at least two local surfaces are superimposed to obtain the total pressure at the local block. The total pressure at the local block is multiplied by the force sharing coefficient to obtain the maximum water pressure at the local block. The water pressure formula is as follows: , Where P is the local pressure, p is the density of water, g is the acceleration due to gravity, and h is the liquid level difference at the local surface.

[0026] The local surface can be either planar or curved. For planar surfaces, the above processing method yields the same result as direct overall processing. For curved surfaces, it is necessary to know the magnitude of the water pressure on the front of the local block, i.e., the water pressure along the feature line direction of the local block. Since the curved surfaces on the front and back sides of the local block are consistent, the front surface is used for calculation. The direction of the water pressure at each point on the front surface is along the normal direction of the tangent plane at that point. Therefore, it is necessary to calculate its contribution in the feature line direction of the local block, i.e., multiply the pressure of the local surface by the area of ​​the corresponding target surface. Thus, the total pressure at the local block can be obtained by superposition. The total pressure is along the feature line direction of the local block. In order to obtain the maximum water pressure at the local block, it is also necessary to multiply it by the force sharing coefficient.

[0027] Reference Figure 5As shown, based on the upper limit of the force, the analysis to obtain the upper limit of the lateral stress of the local block includes the following steps: The distance between the center of the front surface and the center of the rear surface of the local block is taken as the thickness of the local block. The upper limit of the force is divided by the thickness of the local block and the area of ​​the front surface of the local block in turn to obtain the reference pressure. The upper limit of the lateral stress of the local block is obtained by multiplying the reference pressure by the width of the local block and the area of ​​the left surface of the local block.

[0028] The pressure bearing capacity is related to its thickness; the thicker the block, the greater the pressure it can bear. Therefore, dividing the upper limit of the force by the front surface area of ​​the local block gives the pressure acting on the front. Dividing this by the thickness of the local block gives the reference pressure. Multiplying the reference pressure by the width of the local block gives the pressure that can be borne in the left and right directions. Multiplying this by the left surface area of ​​the local block gives the upper limit of the lateral stress of the local block.

[0029] Reference Figure 6 As shown, dividing the local block into target local blocks and non-target local blocks based on the upper limit of lateral stress includes the following steps: Randomly select one of at least two local blocks as the feature local block. The local block set is initially empty. Fill the local block set with the feature local block. Add elements to the local block set by adding all local blocks that are adjacent to one of the local blocks in the local block set on the left or right until no more elements are added to the local block set. When the feature local block traverses all local blocks, at least two local block sets are formed; Substituting the maximum water pressure of the local block into the stress function of the local block, we obtain the estimated lateral stress of the local block. The estimated lateral stress values ​​of the local blocks in the local block set are superimposed to obtain the judgment value of the local block set; If the upper limit of the lateral stress of a local block in the local block set is less than the judgment value of the local block set, then the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block.

[0030] The local blocks in the set are actually adjacent local blocks in the dam body. When stress is generated in the left and right directions, a resultant force will be generated in these local blocks. It is similar to the resultant force in a tug-of-war, where each person's force will make the rope tighter. These resultant forces will act on each local block in the set. Therefore, the upper limit of the lateral stress of each local block in the set should not be less than the judgment value of the set. Otherwise, it means that the local block cannot withstand the stress for a long time and thus needs to be optimized.

[0031] Reference Figure 7As shown, forming at least two thickened areas on the surface of the reservoir dam, based on the target local block, includes the following steps: The surface with the higher water level on the front and rear surfaces of the reservoir dam is used as the reference surface; The intersection of the feature line of the target local block and the reference surface is used as the reference point. A thickened region is formed on the reference surface, so that the thickened region is consistent with the front surface of the target local block, and the center of the thickened region coincides with the reference point.

[0032] Here, the thickened area is determined based on the direction of water pressure on the target local block.

[0033] Reference Figure 8 As shown, the analysis to obtain the minimum thickening thickness of the thickened region includes the following steps: Based on historical construction data, the minimum variation value of the thickness is obtained, and the initial value of the thickness of the thickened area is equal to the minimum variation value. Step 1: Update the stress sharing coefficient of the local block. If the feature line of the local block passes through the thickened area, divide the thickness of the thickened area by the thickness of the local block to obtain the added value. Add the added value to the feature value of the local block to obtain the updated feature value of the local block. Use the reciprocal of the updated feature value of the local block as the updated stress sharing coefficient of the local block. Otherwise, the updated stress sharing coefficient of the local block is equal to the stress sharing coefficient of the local block. Step 2: Multiply the stress sharing coefficient of the local block by the total pressure at the local block to obtain the maximum value of the renewal water pressure at the local block. Substitute the maximum value of the renewal water pressure of the local block into the stress function of the local block to obtain the estimated value of the renewal lateral stress of the local block. Step 3: Superimpose the updated lateral stress estimates of the local blocks in the local block set to obtain the updated judgment value of the local block set; If the upper limit of the lateral stress of a local block in a local block set is less than the update judgment value of the local block set, the thickness of the thickened region is changed and updated. Each change and update increases the thickness of the thickened region by the minimum change value. After the change and update, steps one to three are repeated until there is no local block in a local block set whose upper limit of the lateral stress is less than the update judgment value of the local block set. The current thickness of the thickened region is taken as the minimum thickness of the thickened region.

[0034] Thickening the area, as long as the thickness is sufficient, will inevitably reduce the stress on the target local block and thus meet the requirements. However, infinite thickening will waste materials. Therefore, it is necessary to determine the minimum thickness of the thickened area. Since the thickness variation during construction is discrete and there is a minimum variation value, the thickness of the thickened area is increased by the minimum variation value each time, and the situation after each variation is analyzed to determine whether the target local block still exists. The method of judgment is the same as the method mentioned above. When the target local block does not exist, it means that each local block can bear the generated stress and thus meets the requirements. The thickness of the thickened area at this time is the minimum thickness of the thickened area.

[0035] Reference Figure 9 As shown, the optimization of the model to be optimized based on the minimum thickness includes the following steps: The thickened area is rotated to a horizontal position and designated as the feature area. The column formed by vertically moving the feature area by a distance equal to twice the minimum thickness of the thickened area is designated as the feature body. The center of the top surface of the feature body is taken as the first feature point, and the center of the bottom surface of the feature body is taken as the second feature point; The line connecting the first feature point and the second feature point is used as the baseline. Sampling points are obtained on the baseline such that the maximum value of the sampling point to the bottom edge of the feature body is equal to the distance from the sampling point to the first feature point. A feature sphere is formed with the sampling point as the center and the distance from the sampling point to the first feature point as the radius. The part where the feature sphere and the feature body overlap is taken as the thickened part, and the surface where the thickened part overlaps with the bottom surface of the feature body is taken as the bottom surface of the thickened part. Move the bottom surface of the thickened part to cover the corresponding thickened area, and merge the moved two thickened parts with the model to be optimized to complete the optimization.

[0036] When thickening, if a column is formed directly, the water flow will wear down the edges of the column, turning it into a smooth curved surface, similar to a pebble. To avoid this, a spherical part is used as the thickening part. However, this reduces the actual overall thickness. Therefore, the height of the thickening part is set to twice the minimum thickening thickness. As a result, the overall height of the thickening part will not be lower than the minimum thickening thickness, and its surface is a smooth curved surface, which greatly reduces wear.

[0037] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is invoked, it executes the aforementioned intelligent optimization design method for stress distribution in a reservoir dam body.

[0038] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0039] In summary, the advantages of this invention are as follows: by forming the stress function of a local block, obtaining the stress sharing coefficient of the local block, obtaining the maximum water pressure at the local block, and forming a thickened area and its minimum thickening thickness, it is possible to estimate the transverse stress generated by the dam body under water pressure under the maximum water level during the high-water season, and to combine the resultant force generated by the stress. This allows for the analysis of the target local block with stress bearing defects by combining the hardness of various locations of the dam. Furthermore, based on the location of the target local block, targeted thickening is carried out at the target local block. Thus, under limited structural modification conditions, structural optimization for stress can be completed with high optimization accuracy, meeting the usage requirements.

[0040] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for intelligent optimization design of stress distribution in a reservoir dam body, characterized in that, include: A 3D model of the reservoir dam body is created to obtain the model to be optimized. The model to be optimized is then uniformly divided into at least two local blocks with equal height and width. The target material used in the local blocks is then obtained. Based on the target material, the stress function of a local block is formed, and the upper limit of the force on the local block is obtained through analysis. Obtain the maximum water level in the basin where the reservoir dam is located, perform stress analysis on the model to be optimized, and obtain the stress sharing coefficient of the local block; Based on the maximum water level and the stress sharing coefficient, the maximum water pressure at the local block is obtained through analysis, and based on the upper limit of the stress, the upper limit of the lateral stress at the local block is obtained through analysis. Based on the upper limit of lateral stress, the local blocks are divided into target local blocks and non-target local blocks; Based on the target local block, at least two thickened areas are formed on the surface of the reservoir dam; The minimum thickness of the thickened region is obtained through analysis, and the model to be optimized is optimized based on the minimum thickness. The stress function for forming a local block based on the target material includes the following steps: Based on the historical stress data of the existing reservoirs, the range of stress values ​​for local blocks is obtained; Divide the stress range into equal intervals to obtain at least two test points, set up a sample block, and make the sample block and the local block the same size and shape, and the sample block and the local block the same material. Place the back of the sample block against the wall, and set up force gauges on both sides of the sample block. Under the condition that the force on the front of the sample block is equal to the value of the test point, obtain the reading of the force gauges. Take the average of the readings of the two force gauges to obtain the measured reading. The stress function of the local block is obtained by pairing and fitting the test point values ​​with the measured readings; The process of dividing local blocks into target local blocks and non-target local blocks based on the upper limit of lateral stress includes the following steps: Randomly select one of at least two local blocks as the feature local block. The local block set is initially empty. Fill the local block set with the feature local block. Add elements to the local block set by adding all local blocks that are adjacent to one of the local blocks in the local block set on the left or right until no more elements are added to the local block set. When the feature local block traverses all local blocks, at least two local block sets are formed; Substituting the maximum water pressure of the local block into the stress function of the local block, we obtain the estimated lateral stress of the local block. The estimated lateral stress values ​​of the local blocks in the local block set are superimposed to obtain the judgment value of the local block set; If the upper limit of the lateral stress of a local block in the local block set is less than the judgment value of the local block set, then the local block is regarded as the target local block; otherwise, the local block is regarded as a non-target local block. The analysis to determine the minimum thickness of the thickened region includes the following steps: Based on historical construction data, the minimum variation value of the thickness is obtained, and the initial value of the thickness of the thickened area is equal to the minimum variation value. Step 1: Update the stress sharing coefficient of the local block. If the feature line of the local block passes through the thickened area, divide the thickness of the thickened area by the thickness of the local block to obtain the added value. Add the added value to the feature value of the local block to obtain the updated feature value of the local block. Use the reciprocal of the updated feature value of the local block as the updated stress sharing coefficient of the local block. Otherwise, the updated stress sharing coefficient of the local block is equal to the stress sharing coefficient of the local block. Step 2: Multiply the stress sharing coefficient of the local block by the total pressure at the local block to obtain the maximum value of the renewal water pressure at the local block. Substitute the maximum value of the renewal water pressure of the local block into the stress function of the local block to obtain the estimated value of the renewal lateral stress of the local block. Step 3: Superimpose the updated lateral stress estimates of the local blocks in the local block set to obtain the updated judgment value of the local block set; If the upper limit of the lateral stress of a local block in a local block set is less than the update judgment value of the local block set, the thickness of the thickened region is changed and updated. Each change and update increases the thickness of the thickened region by the minimum change value. After the change and update, steps one to three are repeated until there is no local block in a local block set whose upper limit of the lateral stress is less than the update judgment value of the local block set. The current thickness of the thickened region is taken as the minimum thickness of the thickened region.

2. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 1, characterized in that, The analysis to obtain the upper limit of the force on the local block includes the following steps: Place the back of the sample block against the wall and apply pressure to the front of the sample block. When a crack appears in the sample block, the current applied pressure is taken as the upper limit of the force on the local block.

3. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 2, characterized in that, The process of performing stress analysis on the model to be optimized to obtain the stress sharing coefficient of local blocks includes the following steps: The center of the front surface of the local block is identified, and a tangent plane is drawn at the center of the front surface to obtain the feature plane. Draw the normal to the feature plane at the center of the front surface to obtain the feature line. Take the number of all local blocks that the feature line passes through as the feature value of the local block. The reciprocal of the eigenvalues ​​of the local block is used as the force-sharing coefficient of the local block.

4. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 3, characterized in that, The method for analyzing and determining the maximum water pressure at a local block based on the maximum water level and the stress distribution coefficient includes the following steps: The front surface of the local block is evenly divided into at least two local surfaces. The center of the local surface is identified. The difference between the maximum water level height and the height of the center of the local surface is used to obtain the liquid level difference of the local surface. The pressure on the local surface is calculated using the water pressure formula. The projection of the local surface onto the characteristic plane is taken as the target surface. The pressure of the local surface is multiplied by the area of ​​the corresponding target surface to obtain the pressure value of the local surface. The pressure values ​​of at least two local surfaces are superimposed to obtain the total pressure at the local block. The total pressure at the local block is multiplied by the force sharing coefficient to obtain the maximum water pressure at the local block. The water pressure formula is as follows: ， Where P is the local pressure, p is the density of water, g is the acceleration due to gravity, and h is the liquid level difference at the local surface.

5. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 4, characterized in that, The method of analyzing and obtaining the upper limit of lateral stress in a local block based on the upper limit of force includes the following steps: The distance between the center of the front surface and the center of the rear surface of the local block is taken as the thickness of the local block. The upper limit of the force is divided by the thickness of the local block and the area of ​​the front surface of the local block in turn to obtain the reference pressure. The upper limit of the lateral stress of the local block is obtained by multiplying the reference pressure by the width of the local block and the area of ​​the left surface of the local block.

6. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 5, characterized in that, The process of forming at least two thickened regions on the surface of the reservoir dam based on the target local block includes the following steps: The surface with the higher water level on the front and rear surfaces of the reservoir dam is used as the reference surface; The intersection of the feature line of the target local block and the reference surface is used as the reference point. A thickened region is formed on the reference surface, so that the thickened region is consistent with the front surface of the target local block, and the center of the thickened region coincides with the reference point.

7. The intelligent optimization design method for stress distribution in a reservoir dam body according to claim 6, characterized in that, The optimization of the model to be optimized based on the minimum thickness includes the following steps: The thickened area is rotated to a horizontal position and designated as the feature area. The column formed by vertically moving the feature area by a distance equal to twice the minimum thickness of the thickened area is designated as the feature body. The center of the top surface of the feature body is taken as the first feature point, and the center of the bottom surface of the feature body is taken as the second feature point; The line connecting the first feature point and the second feature point is used as the baseline. Sampling points are obtained on the baseline such that the maximum value of the sampling point to the bottom edge of the feature body is equal to the distance from the sampling point to the first feature point. A feature sphere is formed with the sampling point as the center and the distance from the sampling point to the first feature point as the radius. The part where the feature sphere and the feature body overlap is taken as the thickened part, and the surface where the thickened part overlaps with the bottom surface of the feature body is taken as the bottom surface of the thickened part. Move the bottom surface of the thickened part to cover the corresponding thickened area, and merge the moved two thickened parts with the model to be optimized to complete the optimization.

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