CN112733238B - Pile position optimization method for high pile pier platform - Google Patents
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Abstract
The invention discloses a high pile abutment pile position optimization method, which comprises the following steps of 1) modeling a high pile abutment which is preliminarily designed according to actual project requirements in finite element calculation software; 2) carrying out weight setting on the internal force of the pile foundation and setting a target value function; 3) and integrating an optimization method based on a genetic algorithm with a finite element model calculation process through programming to realize automatic iterative optimization of the program. The invention uses genetic algorithm as basic method, uses finite element calculation software as basic tool, realizes the design method of automatically optimizing the pile position arrangement by computer, greatly saves manpower, and obtains the pile position arrangement which is better than the manually designed pile position in the aspect of pile foundation internal force. The problems of low efficiency and poor result in the traditional pile position design process are solved, a large amount of labor can be saved, and the pile position arrangement which is more excellent than the manually designed pile position in the pile foundation internal force is obtained. The method has the advantages of high implementation efficiency, less time required by iteration, obvious optimization effect and easy popularization and use in port engineering design.
Description
Technical Field
The invention relates to the technical field of port construction engineering, in particular to a design method of a pile position of a high pile pier platform.
Background
In port engineering, a mooring pier mainly bears loads such as dead weight, mooring force and ship-berthing force. For the mooring pier in the form of a high pile abutment, the pile foundation needs to be checked for pile body strength and pile foundation bearing capacity. The pile body strength is mainly used for checking and calculating the bending combination and integral buckling of pile pressing force and bending moment. The bearing capacity of the pile foundation is mainly used for checking and calculating the relation between the pile pressing force, the pile pulling force and the axial resistance provided by the geology. In the pile position arrangement design process, the axial force of the inclined pile can effectively reduce pile body bending moment caused by horizontal forces such as mooring force, impact force and the like, and the requirement on the strength of the pile body is reduced. However, if the pile position of the inclined pile is not properly arranged, large pile pressing and pulling force can be generated, and when the geological conditions are poor, soil around the pile cannot provide enough resistance, so that the structure fails. Therefore, the reasonable arrangement of the pile positions can effectively reduce the internal force of the pile foundation, reduce the requirement on the strength of the pile body and the requirement on the bearing capacity of the foundation, and thus, less piles are used for bearing the same load.
The arrangement of the pile positions mainly comprises the spacing of the piles, the inclination of the piles and the torsion angle of each pile. The pitch and inclination of the piles is less variable, and the general difficulty in pile placement is how the twist angle of each pile should be arranged. Assuming a 12-pile abutment, the torsion angle of each pile varies in a range of 360 °, and there are 24 possibilities for each pile even with 15 ° as the minimum torsion angle, and a rough estimate of the 24-power possibility of 12 pile positions indicates that the optimal solution cannot be obtained by the method of the past. The previous pile position design is a mechanical process of repeated iteration, and even an engineer with more experience cannot ensure that a better result can be obtained by each adjustment. The arrangement of pile positions and the internal force distribution of piles are complex nonlinear relations, wherein the angle adjustment of one pile can cause the internal force of each other pile to have a large or positive or negative influence. This makes the in-process of adjusting the stake position often appear repeatedly, repeated adjustment, is comparatively loaded down with trivial details, tired work to the engineer. Even in order to avoid pile collision, a pile position sketch needs to be drawn, so that one-time pile position adjustment needs to consume much time.
On the other hand, in the process of adjusting the pile position, as the value to which the internal force of the pile foundation can be reduced for the optimal pile position is an unknown number, for an engineer, the optimal internal force value is usually judged by experience, and the limit value according to the pile strength and the foundation bearing capacity is used as the target of pile position adjustment. Once this goal is reached, the stake position arrangement is deemed to meet the requirements and no more optimal stake positions are pursued. If objectively there may be a certain degree of better stake placement, the placement of the stake selected by the engineer is not yet the most economical. If the pile position is more optimal, design parameters such as the section size, the pile length and the like of the pile can be reduced, so that the design of the high pile pier structure is more competitive.
In summary, since the conventional pile position design process requires a lot of manpower and material resources, and the result is often a certain difference from the optimal design, it is significant to provide a method for automatically and repeatedly searching the sub-optimal solution of the pile position design by the computer program.
Disclosure of Invention
The invention aims to solve the technical problems that the traditional pile position design process is low in efficiency and the design result often has an optimization space, and provides a method which is based on genetic algorithm and computer programming and can optimize the pile position of a high pile pier platform more efficiently and more optimally.
In order to solve the technical problems, the invention adopts the following technical scheme: a pile position optimization method for a high pile pier platform is characterized by comprising the following steps: the method comprises the following steps of (1),
1) modeling the high-pile abutment preliminarily designed according to the actual project requirements in finite element calculation software;
2) carrying out weight setting on internal forces of the pile foundation, such as pile pressing force, pile pulling force and bending moment, and setting a target value function;
3) integrating the following optimization method based on genetic algorithm with the finite element model calculation process in a programming mode to realize automatic iterative optimization of the program, wherein the optimization process is as follows:
(1) setting optimization parameters; (2) randomly generating an initial pile position population table; (3) the finite element analysis software is controlled by program codes to automatically model the pile position members one by one and calculate the target value of the internal force of the pile foundation; (4) sorting each pile position member according to a target value; (5) taking a certain number of stake position members with the top rank as elite members, and reserving the elite members until the next generation; (6) removing the other members after ranking out of the population table, taking elite members for hybridization or variation to form new pile position members, and supplementing the population table to form a new pile position population table; (7) and (5) circulating the process (3) to the process (6) until the optimization ending condition is met, and obtaining the optimized pile position arrangement with the smaller internal force level.
The pile position refers to the torsion angle distribution condition of each pile of one pier structure.
The target value function in step 2) takes the following form:
Cost＝Wp·|Fp|Wc·|Fc|+Wm·|Fm|
where Cost is the target value, Fp、Fc、FmRespectively, the maximum pile pulling force, pile pressing force and bending moment internal force value, W, of the high pile pier platform pile foundation obtained under each load working conditionp、Wc、WmThe weights are respectively corresponding to the maximum pile pulling force, the pile pressing force and the bending moment.
Based on the target value function, the size proportion of the internal force (such as pile pressing force, pile pulling force and bending moment) of each pile foundation in the optimization result can be controlled according to the geological conditions (such as the side friction resistance and the end resistance in the bearing capacity of the pile foundation) and the allowable pile strength value.
And 3) integrating an optimization method based on a genetic algorithm with a finite element model calculation flow, wherein the finite element software for realizing automatic iterative optimization of the program can be common finite element calculation software ANSYS, SAP, LUSAS, MIDAS and the like, and the programming method can be programming languages such as C + +, VB, Python and the like, and can also be methods such as command streams, macro files and the like carried by the finite element software. And (3) realizing a loop iteration process of programmed automatic modeling, calculation, post-processing and optimization iteration through programming.
The optimization parameters in the process (1) in the step 3) specifically include: the elite ratio refers to the ratio of elite members in each generation of population to all members; the population scale refers to the total number of population members; the variation ratio refers to the probability that the elite member in each generation of population generates variation to generate a new member, and the sum of the variation ratio and the hybridization ratio is 1; the hybridization proportion refers to the probability of generating new members by hybridization of elite members in each generation of population; the variation strength refers to the number of variant piles of a certain variant elite member; iteration number refers to the total number of iterations in the optimization process.
The pile position population table and the generation method thereof in the processes (2) and (6) in the step 3) are as follows: when a pile position arrangement member is formed, the distance between piles is calculated by adopting a method of calculating the distance between two spatial straight lines in solid geometry, and whether the piles touch the piles or not is judged. Because the piles are line segments instead of straight lines, the distance relationship between the quartering points between the two piles is judged to further judge whether the two piles touch the piles, and the method specifically comprises the following steps: pile strike conditions exist when either of the following conditions exist: a. the distance between the pile tops of two piles is less than the diameter of the pile; b. the distance between the pile bottoms of two piles is less than the diameter of the pile; c. the distance between the top and the bottom of two piles is greater than the diameter of the pile, but the distance between the quarter point and the half point, or between the half point and the third point is less than the diameter of the pile.
And directly eliminating the pile position with the pile collision, and regenerating a new pile position member until the newly generated pile position member does not have the pile collision condition. Finally, a certain number of pile position members are generated to fill the pile position population table.
The hybridization in the flow (6) in the step 3) is two or more elite members, and each elite member is partially taken to form a new and complete pile position without pile collision. The twisting angle of partial pile is changed randomly (the number of changed piles is controlled by the variation strength) to form a new pile position without pile collision.
After the method is adopted, the problems of low efficiency and poor result of the traditional pile position design process are solved, the genetic algorithm is used as a basic method, finite element calculation software is used as a basic tool, and the design method for automatically optimizing the pile position arrangement by a computer is realized through computer programming. The method has the advantages of high implementation efficiency, less time required by iteration, obvious optimization effect and easy popularization and use in port engineering design by means of computer languages.
Drawings
FIG. 1 is a schematic diagram of a finite element model of a high pile abutment in an embodiment of the invention;
FIG. 2 is a flowchart of a stake position optimization method in an embodiment of the present invention;
FIG. 3 is a first generation population elite membership target value in an embodiment of the present invention;
FIG. 4 is a graph of elite membership target values of a tenth generation population in an example of the present invention;
FIG. 5 is a representation of elite membership target values in the twentieth generation population in an example of the present invention;
fig. 6 shows the target value of each generation of the optimal elite member pile foundation in the embodiment of the invention.
Detailed Description
In the embodiment, general finite element software ANSYS is used as structural calculation software, and APDL command streams carried by the ANSYS are used for writing structural modeling, calculation, post-processing and iterative optimization codes. This example is only for the further detailed description of the present invention, but does not constitute any limitation to the present invention.
The high pile abutment pile position optimization method comprises the following steps of 1) modeling high pile abutments designed primarily in finite element calculation software:
in this embodiment, in the finite element model, the upper concrete pier is simulated by the shell unit, the pile foundation is simulated by the beam unit, the pile-soil interaction is the consolidation point method, the load considers the structure dead weight and the mooring force, wherein the mooring force is 4500kN, the included angle range with the horizontal plane is 0-45 degrees, the included angle range with the front line of the pier is 60-120 degrees, and the finite element model is as shown in fig. 1.
2) Carrying out weight setting on the internal force of the pile foundation and setting a target value function;
the objective function is set as follows:
Cost＝Wp·|Fp|+Wc·|Fc|+Wm·|Fm|
where Cost is the target value, Fp、Fc、FmRespectively, the maximum pile pulling force, pile pressing force and bending moment internal force values of the pile foundation of the high pile pier platform; wp、Wc、WmThe weights corresponding to the maximum pile pulling force, pile pressing force and bending moment are respectively set as 4, 1.7 and 6 in the embodiment.
3) Integrating the following optimization method based on genetic algorithm with the finite element model calculation process in a programming mode to realize automatic iterative optimization of the program, wherein the optimization process is as follows:
(1) the present embodiment employs the following optimization parameters:
elite ratio of 0.4, population size of 20, variation ratio of 0.4, hybridization ratio of 0.6, variation intensity of 2, and alternation number of 20. The optimization termination condition is that the optimization termination condition is terminated when the iteration number is satisfied.
(2) And generating a random initial stake position population table by a code, wherein the table is shown in a table 1.
(3) And (3) controlling finite element analysis software through program codes to automatically model each pile position member in the pile position population table in the flow (II) one by one, and calculating the internal force and the target value to obtain a pile foundation internal force table of each member, wherein the table is shown as table 1.
(4) Table 1 was sorted by target value to give Table 2.
TABLE 1 initial pile position population table each member pile foundation internal force
TABLE 2 internal force of pile foundations of each member of initial pile position population table after sequencing
(5) The first 20 x 0.4 ═ 8 (population size/elite ratio) of the stake site members in table 2 were elite members, and the next 12 members were directly eliminated.
(6) 12 new members with no stump hits were generated among 8 elite members by crossing or mutation, and the population table was completed. Before generating a new member, firstly generating a random number in the range of 0-1, carrying out mutation when the random number is smaller than the mutation ratio, and carrying out hybridization when the random number is larger than the mutation ratio. Wherein, the variation is that 2 (variation strength) piles are randomly selected on the basis of a certain optional elite member, and the torsion angle of the piles is randomly changed; and in the hybridization step, two or more elite members are selected optionally, and part of pile foundation torsion angles of the members are randomly selected and are filled to form a new pile position. The pile collision detection method comprises the following two methods: a. and b, calculating the distance between two straight lines in the space, and calculating the distance between four points of the line segment. And if the pile is hit, a new member is regenerated in the same method until the pile hitting situation does not exist.
(7) And (4) carrying out internal force calculation on each pile position member in the filled pile position population table, repeating the processes (3) to (6), and sequentially circulating until the iteration number reaches 20 (an alternate generation number), wherein the process is shown in the attached figure 2.
In this embodiment, the target values of the first, tenth and twentieth generation elite members are shown in fig. 3, fig. 4 and fig. 5, and the target values of the pile foundations of the optimal elite members in each generation are shown in fig. 6.
After the iteration is completed, the torsion angle and internal force of the best member in the twentieth generation population are as shown in table 3. The elite members in the final generation population are also the better members, and the stake position arrangement thereof can be referred by designers.
TABLE 3 torsion angle and internal force of the best members in the twentieth generation population
The optimization process of the embodiment is a simple calculation example for testing, the number of the piles is 9, the minimum rotation torsion angle is 15 degrees, the number of the alternate generations is 20, the population scale is 20, the calculation time is about 10 minutes, an ideal internal force value can be obtained, and the method has considerable superiority in time and labor cost compared with manual pile position debugging.
According to the geological condition, the weight value of each internal force is set by factors such as the material strength of the steel pipe pile and the like, the bearing capacity provided by the pile foundation is utilized to the maximum extent, the economic rationality of the design scheme is effectively improved, and the competitiveness of the high pile pier scheme is improved.
The present invention has been described in detail, and it should be understood that the detailed description and specific examples, while indicating the preferred embodiment of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
Claims (5)
1. A pile position optimization method for a high pile pier platform is characterized by comprising the following steps: the method comprises the following steps of (1),
1) modeling the high-pile abutment preliminarily designed according to the actual project requirements in finite element calculation software;
2) carrying out weight setting on the internal force of the pile foundation and setting a target value function;
3) the following optimization method based on genetic algorithm is integrated with the finite element model calculation process through programming to realize automatic iterative optimization of the program, and the optimization process is as follows:
(1) setting optimization parameters;
(2) randomly generating an initial pile position population table;
(3) the finite element analysis software is controlled by program codes to automatically model the pile position members one by one and calculate the target value of the internal force of the pile foundation;
(4) sorting each pile position member according to a target value;
(5) taking a certain number of stake position members with the top rank as elite members, and reserving the elite members until the next generation;
(6) removing the other members after ranking out of the population table, taking elite members for hybridization or variation to form new pile position members, and supplementing the population table to form a new pile position population table;
(7) the process (3) to the process (6) are circulated until the optimization ending condition is met, and the optimized pile position arrangement with smaller internal force level can be obtained;
in the step 2), the target value function sets different weights for the internal force of each pile foundation, and based on the target value function, the size proportion of the internal force value of each pile foundation in the optimization result is controlled according to the geological condition and the pile strength allowable value; the geological condition comprises the side friction resistance and the end resistance in the bearing capacity of the pile foundation, and the internal force of the pile foundation comprises pile pressing force, pile pulling force and bending moment;
the target value function adopts the following function:
wherein the content of the first and second substances,
in order to achieve the target value,
、
、
the maximum pile pulling force, pile pressing force and bending moment internal force values of the high pile pier platform pile foundation are obtained under various load working conditions respectively,
、
、
the weights are respectively corresponding to the maximum pile pulling force, the pile pressing force and the bending moment.
2. The method for optimizing the pile position of the high pier table according to claim 1, wherein: in step 3), the finite element software integrating the optimization method based on the genetic algorithm and the finite element model calculation process comprises ANSYS, SAP, LUSAS and MIDAS, the programming method is a command stream and a macro file carried by a programming language or the finite element software, and the programming method is used for realizing a loop iteration process of programmed automatic modeling-calculation-post-processing-optimization iteration.
3. The method for optimizing the pile position of the high pier table according to claim 1, wherein: the optimization parameters of the process (1) in the step 3) comprise: elite ratio, population size, variation ratio, hybridization ratio, and variation intensity.
4. The method for optimizing the pile position of the high pier table according to claim 1, wherein: the generation method of the pile position population table in the processes (2) and (6) in the step 3) comprises the following steps: when a pile position arrangement member is formed, calculating the distance between piles by adopting a method of calculating the distance between two spatial straight lines in solid geometry, and judging whether the piles touch the piles or not; because the piles are line segments instead of straight lines, whether the two piles touch the piles can be further judged by judging the distance relationship between the four points between the two piles; and (4) directly eliminating the pile positions with pile collision, regenerating new pile position members until the newly generated pile position members do not have the pile collision condition, and finally generating a certain number of pile position members to fill the pile position population table.
5. The method for optimizing the pile position of the high pier table according to claim 1, wherein: in the step 3), the hybridization in the flow (6) is two or more elite members, and each elite member is partially positioned to form a new and complete pile position without pile collision; the variation is a certain elite member, the torsion angles of partial piles of the elite member are randomly changed to form a new pile position without the pile collision condition, and the number of the randomly changed piles is controlled by the variation strength.
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| CN104102779A (en) * | 2014-07-18 | 2014-10-15 | 同济大学 | Energy dissipation and shock absorption optimization design method |
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