CN115859434A - Method and device for designing stay cable of steel and carbon fiber hybrid stay cable bridge - Google Patents
Method and device for designing stay cable of steel and carbon fiber hybrid stay cable bridge Download PDFInfo
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Abstract
The application relates to the technical field of bridge design, in particular to a method and a device for designing a steel and carbon fiber hybrid stay cable of a cable-stayed bridge, wherein the method comprises the following steps: determining basic geometric parameters and basic load parameters of a cable-stayed bridge, determining cable characteristic data of the steel and carbon fiber mixed cable, the maximum cable type number and cable specification selection table of various types of cables, performing optimization calculation based on a genetic algorithm and a deep learning mode to obtain the fitness of each individual in the t generation population, and performing calculation until preset iteration or termination calculation conditions are reached to obtain the individual with the highest fitness of the population and obtain an optimized numerical solution. The embodiment of the application can reasonably set genetic algorithm parameters and integrate deep learning mode prediction, so that the estimation efficiency of the cable strength value is improved, the cable force of the cable-stayed bridge can be calculated more accurately, the automatic and efficient design of the cable is realized, and the applicability is stronger.
Description
Technical Field
The application relates to the technical field of bridge design, in particular to a method and a device for designing a stay cable of a steel and carbon fiber hybrid stay cable-stayed bridge.
Background
In the design of a bridge, a tower, a beam and a guy cable are used as main stress components, the guy cable directly bears the gravity, and the bridge with a main beam bearing the axial force and the local bending moment is called a cable-stayed bridge. The cable-stayed bridge belongs to a multi-constraint hyperstatic structure, a plurality of stay cables are provided, the cable force is adjustable, and various bridge-forming stress states meeting requirements exist.
In the related art, the stay cable of the cable-stayed bridge at the current stage generally adopts steel as a main material, and the cable-stayed bridge simultaneously adopts a carbon fiber composite stay cable and a steel stay cable, wherein the carbon fiber composite stay cable has the characteristics of high strength, light weight, small sag and the like, so that the span of the cable-stayed bridge with the steel and carbon fiber mixed stay cable is larger.
However, in the related art, the non-linear degree of the steel and carbon fiber hybrid cable-stayed bridge is higher, the constraint is more, and during the hybrid arrangement, the difference in rigidity between the cables larger than that of the single-material cable-stayed bridge may be generated, resulting in the increase of difficulty in adjusting the cable force of the cable-stayed bridge, the calculation efficiency of the cable-stayed bridge design process is reduced, and the rapid and efficient design of the steel and carbon fiber hybrid cable-stayed bridge cable cannot be realized, which is urgently needed to be solved.
Disclosure of Invention
The application provides a design method and a device for a steel and carbon fiber hybrid stay cable of a cable-stayed bridge, and aims to solve the problems that in the related art, the non-linear degree of the steel and carbon fiber hybrid stay cable-stayed bridge is higher, the restraint is more, and in the hybrid arrangement process, the rigidity difference between the stay cables which is larger than that of a single-material stay cable-stayed bridge is possibly generated, the adjustment difficulty of the cable force of the cable-stayed bridge is increased, the calculation efficiency in the design process of the stay cable of the cable-stayed bridge is reduced, and the fast and efficient design of the steel and carbon fiber hybrid stay cable-stayed bridge cannot be realized.
The embodiment of the first aspect of the application provides a method for designing a steel and carbon fiber hybrid stay cable of a cable-stayed bridge, which comprises the following steps: determining basic geometric parameters and basic load parameters of the cable-stayed bridge, and determining cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number and cable specification selection table of various types of cables; based on a genetic algorithm and a deep learning mode, carrying out optimization calculation according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable variety quantity and the inhaul cable specification selection table to obtain the fitness of each individual in the population of the t generation, wherein t is a positive integer; matching the selected probability of each individual based on the fitness of each individual in the population of the t generation, acting a crossover operator on the population, and acting a mutation operator on the population until a preset iteration or a termination operation condition is reached to obtain the individual with the highest fitness of the population, and decoding the chromosome of the highest individual to obtain an optimized numerical solution.
Optionally, in an embodiment of the present application, the performing, based on a genetic algorithm and a deep learning manner, an optimization calculation according to the basic geometric parameter, the basic load parameter, the guy cable characteristic data, the maximum guy cable type number, and the guy cable specification selection table to obtain the fitness of each individual in the population of the tth generation includes: selecting cable force within a preset range of estimated cable force, forming an individual based on the cable force of all full-bridge cables, enabling each individual to correspond to a chromosome, setting a maximum evolution algebra, and randomly generating a plurality of individuals as an initial population; and calculating the initial fitness of each individual in the t-th generation population.
Optionally, in an embodiment of the present application, the calculating an initial fitness of each individual in the population of the tth generation includes: estimating initial constant load cable force of the plurality of stay cables according to the constant load; estimating initial live load cable force according to live load; calculating and estimating the specification of the inhaul cable according to the initial dead load cable force and the initial live load cable force; calculating and estimating the constant-load cable stiffness according to the initial constant-load cable force and the estimated cable specification; recalculating the live load maximum cable force according to the estimated constant load cable stiffness; recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live-load maximum cable force; calculating the rigidity of the stay cable according to the initial constant load cable force and the specification of the stay cable; recalculating the final constant-load cable force according to the constant load and the cable rigidity; and acquiring the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
Optionally, in an embodiment of the present application, the calculation formula of the initial live load cable force is:
wherein, F li Estimation of live load Cable force, Δ L, for the ith Cable i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc Concentrated load for live loads, theta i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
Optionally, in an embodiment of the present application, the calculating an estimated cable specification according to the initial dead load cable force and the initial live load cable force includes: and calculating the bridge-forming inhaul cable specification meeting the stress requirement according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle respectively to obtain the estimated inhaul cable specification.
Optionally, in an embodiment of the present application, an expression of the preset least used amount rule is:
wherein n is the number of the stay cables, L i The length of the i-th inhaul cable is N i I =1, 2, …, n for the ith cable number.
The embodiment of the second aspect of the application provides a steel and carbon fiber hybrid cable-stayed bridge cable design device, include: the determining module is used for determining basic geometric parameters and basic load parameters of the cable-stayed bridge, and determining cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number and cable specification selection table of various types of cables; the calculation module is used for carrying out optimization calculation according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable type quantity and the inhaul cable specification selection table based on a genetic algorithm and a deep learning mode to obtain the fitness of each individual in the tth generation population, wherein t is a positive integer; and the acquisition module is used for matching the selected probability of each individual based on the fitness of each individual in the population of the t generation, acting a crossover operator on the population, acting a mutation operator on the population until a preset iteration or operation termination condition is reached, obtaining the individual with the highest fitness of the population, decoding the chromosome of the highest individual, and obtaining an optimized numerical solution.
Optionally, in an embodiment of the present application, the calculation module includes: the generating unit is used for selecting and estimating the cable force within the preset range of the cable force, forming an individual by the cable forces of all the full-bridge cables, enabling each individual to correspond to one chromosome, setting a maximum evolution algebra, and randomly generating a plurality of individuals as an initial population; and the first calculating unit is used for calculating the initial fitness of each individual in the tth generation population.
Optionally, in an embodiment of the present application, the calculation module further includes: the first estimation unit is used for estimating initial constant load cable force of the plurality of stay cables according to the constant load; the second estimation unit is used for estimating the initial live load cable force according to the live load; the second calculation unit is used for calculating and estimating the specification of the inhaul cable according to the initial dead load cable force and the initial live load cable force; the third calculation unit is used for calculating and estimating the constant-load stay cable rigidity according to the initial constant-load stay cable force and the estimated stay cable specification; the fourth calculation unit is used for recalculating the live load maximum cable force according to the estimated constant load cable stiffness; the fifth calculation unit is used for recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live-load maximum cable force; the sixth calculating unit is used for calculating the rigidity of the inhaul cable according to the initial constant-load cable force and the inhaul cable specification; the seventh calculating unit is used for recalculating the final constant load cable force according to the constant load and the cable rigidity; and the obtaining unit is used for obtaining the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
Optionally, in an embodiment of the present application, the calculation formula of the initial live load cable force is:
wherein, F li For evaluation of the ith ropeCalculation of live load cable force, Δ L i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc Concentrated load for live loads, theta i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
Optionally, in an embodiment of the present application, the second computing unit includes: and calculating the specifications of the bridge-forming inhaul cables meeting the stress requirements according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle respectively to obtain the estimated inhaul cable specifications.
Optionally, in an embodiment of the present application, an expression of the preset least used amount rule is:
wherein n is the number of the stay cables, L i The length of the i-th inhaul cable is N i I =1, 2, …, n for the ith cable number.
An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the design method of the steel and carbon fiber hybrid cable-stayed bridge cable according to the embodiment.
An embodiment of a fourth aspect of the present application provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the above cable design method for a hybrid steel and carbon fiber cable-stayed bridge.
The embodiment of the application can determine the basic geometric parameters and the basic load parameters of the cable-stayed bridge, determine the cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type quantity and the cable specification selection table of various types of cables, optimize and calculate based on a genetic algorithm and a deep learning mode, and obtain the fitness of each individual in the t-th generation group, so that the calculation is carried out until the preset iteration or termination calculation condition is reached, the individual with the highest fitness of the group is obtained, an optimized numerical solution is obtained, the estimation efficiency of the cable strength value is improved, the cable force calculation of the cable-stayed bridge can be more accurate, the automatic efficient design of the cable is realized, and the applicability is stronger. Therefore, the problems that in the related art, the non-linear degree of a steel and carbon fiber hybrid stay cable bridge is higher, the restraint is more, and in the hybrid arrangement, the rigidity difference between the stay cables which is larger than that of a single-material stay cable bridge is possibly generated, so that the difficulty of adjusting the stay cable force of the finished bridge is increased, the calculation efficiency of the design process of the stay cable of the cable-stayed bridge is reduced, and the fast and efficient design of the steel and carbon fiber hybrid stay cable bridge stay cable cannot be realized are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a method for designing a cable of a hybrid steel and carbon fiber cable-stayed bridge according to an embodiment of the present application;
FIG. 2 is a process diagram of a steel and carbon fiber hybrid cable-stayed bridge cable design method based on genetic algorithm and deep learning according to an embodiment of the present application;
FIG. 3 is a schematic view of a reference cable-stayed bridge according to an embodiment of the present application;
FIG. 4 is a graph of an iteratively calculated error for a reference cable-stayed bridge according to an embodiment of the present application;
fig. 5 is a graph of safety factor and reliability index curves after a design of a reference cable-stayed bridge according to an embodiment of the present application is completed;
fig. 6 is a line graph of cable force and cable specification before and after cable iteration after a design of a reference cable-stayed bridge according to an embodiment of the present application;
FIG. 7 is a schematic structural diagram of a hybrid steel and carbon fiber cable-stayed bridge cable design device according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The method and the device for designing the steel and carbon fiber hybrid cable-stayed bridge cable according to the embodiment of the application are described below with reference to the accompanying drawings. In the related technology mentioned in the background technology center, the steel and carbon fiber hybrid cable-stayed bridge has higher nonlinear degree and more constraints, and when the hybrid cable-stayed bridge is arranged in a hybrid way, the rigidity difference between the cables is possibly larger than that of a single material cable-stayed bridge, so that the difficulty of adjusting the cable-forming force is increased, the calculation efficiency of the cable-stayed bridge cable design process is reduced, and the problem that the cable-stayed bridge cable cannot be quickly and efficiently designed is solved. Therefore, the problems that in the related art, the non-linear degree of a steel and carbon fiber hybrid stay cable bridge is higher, the restraint is more, and in the hybrid arrangement, the rigidity difference between the stay cables which is larger than that of a single-material stay cable bridge is possibly generated, so that the difficulty of adjusting the stay cable force of the finished bridge is increased, the calculation efficiency of the design process of the stay cable of the cable-stayed bridge is reduced, and the fast and efficient design of the steel and carbon fiber hybrid stay cable bridge stay cable cannot be realized are solved.
Specifically, fig. 1 is a schematic flow chart of a method for designing a steel and carbon fiber hybrid cable-stayed bridge cable according to an embodiment of the present application.
As shown in fig. 1, the method for designing the steel and carbon fiber mixed cable-stayed bridge cable comprises the following steps:
in step S101, determining basic geometric parameters and basic load parameters of the cable-stayed bridge, and determining cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number and cable specification selection table of each type of cable.
It can be understood that, in the embodiment of the present application, the basic geometric parameters of the cable-stayed bridge may define the position relationship of the cable beams of the cable-stayed bridge, and the basic load parameters of the cable-stayed bridge may define the dead load and live load of the cable-stayed bridge, including the mean value and the coefficient of variation. The type of each inhaul cable can be determined according to inhaul cable characteristic data of the steel and carbon fiber hybrid inhaul cable, the inhaul cable can be a steel inhaul cable or a carbon fiber composite inhaul cable, and the calculation method control parameters of each inhaul cable can be material indexes and safety coefficient indexes of the steel inhaul cable or material indexes and reliability indexes of the carbon fiber composite inhaul cable. The cable specification selection table for each type of cable may include properties such as specification, weight, sectional area, etc. of each cable.
In the actual implementation process, when relevant parameters are selected, the stay cable material can be steel, carbon fiber composite material, steel and carbon fiber composite material, the cable surface form can be single cable surface, double cable surfaces, dense cable and sparse cable, and the bridge tower form can be a concrete tower, a steel tower, a single-column tower, a double-column tower and the like.
The method and the device can determine basic geometric parameters and basic load parameters of the cable-stayed bridge, determine cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type quantity and cable specification selection table of various types of cables, and acquire relevant parameters required by an algorithm in the following steps through data preprocessing of cable design, so that a data basis is provided for acquiring cable design results of the cable-stayed bridge.
In step S102, based on a genetic algorithm and a deep learning manner, performing optimization calculation according to the basic geometric parameters, the basic load parameters, the guy cable characteristic data, the maximum guy cable type number, and the guy cable specification selection table to obtain the fitness of each individual in the population of the tth generation, where t is a positive integer.
In the actual execution process, the processing can be carried out according to the relevant data obtained in the steps based on a genetic algorithm, the average value and the variation coefficient of the strength of the carbon fiber composite stay cable are obtained according to the unit strength index obtained from the test data through deep learning prediction, the prediction of the strength value of the carbon fiber composite stay cable is realized, and then the optimized calculation of the data is completed.
According to the method and the device, optimization calculation can be carried out according to basic geometric parameters, basic load parameters, inhaul cable characteristic data, the maximum inhaul cable type quantity and the inhaul cable specification selection table on the basis of a genetic algorithm and a deep learning mode, the fitness of each individual in the t-th generation population is obtained, prediction is carried out through the deep learning mode, corresponding calculation efficiency is improved, and the design process is more efficient.
Optionally, in an embodiment of the present application, based on a genetic algorithm and a deep learning manner, performing optimization calculation according to a basic geometric parameter, a basic load parameter, cable characteristic data, a maximum cable type number, and a cable specification selection table to obtain a fitness of each individual in a population of a t-th generation, including: selecting cable force within a preset range of estimated cable force, forming an individual based on the cable force of all the cables in the full bridge, enabling each individual to correspond to one chromosome, setting a maximum evolution algebra, and randomly generating a plurality of individuals as an initial population; and calculating the initial fitness of each individual in the population of the t generation.
It can be understood that, in the embodiment of the present application, the cable force within the preset range of the estimated cable force can be selected by calculating the estimated constant load cable force values of the cables within a certain range, forming an individual based on the cable forces of all the cables in the full bridge, associating each individual with a chromosome, where the initial constant load cable force is,
wherein, F di Estimated deadweight force, Δ L, for the ith rope i The distance between the cables corresponding to the ith cable, F du For constant uniform load, theta i And (3) an included angle between the ith cable and the horizontal plane is shown, p is a value range of the search cable force, and i =1, 2, … and n. Wherein p may be in the range of 0.8 to 1.2.
For example, binary gray code can be used as a chromosome coding mode, an individual is formed based on the cable force of all cables in the full bridge, each individual corresponds to one chromosome, the chromosomes can cover a preset cable force range, the maximum evolution generation number T is set, and N individuals are randomly generated to serve as an initial population P (0), so that the initial fitness of each individual in the population is calculated.
According to the embodiment of the application, the cable force within the preset range of the estimated cable force can be selected, an individual is formed based on the cable force of all full-bridge cables, each individual corresponds to one chromosome, the maximum evolution algebra is set, a plurality of individuals are randomly generated to serve as an initial population, the initial fitness of each individual in the t generation population is calculated, the parallel computing capability of a computer can be fully utilized through reasonably setting genetic algorithm parameters, and the computing speed is further improved.
Optionally, in an embodiment of the present application, calculating the initial fitness of each individual in the population of the tth generation includes: estimating initial constant-load cable force of the plurality of stay cables according to the constant load; estimating initial live load cable force according to the live load; calculating and estimating the specification of the stay cable according to the initial constant-load cable force and the initial live-load cable force; calculating and estimating the constant-load cable stiffness according to the initial constant-load cable force and the estimated cable specification; recalculating the live load maximum cable force according to the estimated constant load cable stiffness; recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live-load maximum cable force; calculating the rigidity of the stay cable according to the initial constant load cable force and the specification of the stay cable; recalculating the final constant-load cable force according to the constant load and the cable stiffness; and acquiring the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
It can be understood that, in the embodiment of the present application, the initial deadweight cable force may be estimated according to the geometric parameters and the deadweight in the load, and the initial live load cable force may be estimated according to the geometric parameters and the live load in the load.
In the actual execution process, when the genetic algorithm is iterated, each individual can select an input value according to a certain range of the initial constant load cable force obtained by estimation, such as 0.8-1.2, so as to obtain the initial live load cable force, and the next individual selects an initial constant load cable force as the input value again for estimation. And calculating the initial fitness of each individual in the population of the t generation by evaluating the individual, wherein the evaluation function takes all input bridging cable forming forces as input parameters and outputs error indexes of the input bridging cable forming forces and the bridging cable forming forces estimated on the basis of the input bridging cable forming forces.
For example, first, the constant load cable force of N cables can be estimated according to the constant load q to obtain an initial constant load cable force F d As input parameters and according to the live load q l Estimating live load cable force to obtain initial live load cable force F l . Then according to the input initial constant load cable force F d And estimated initial live load cable force F l And calculating and estimating the cable specification omega. From the resulting input initial deadweight cable force F d And estimating the cable specification omega, calculating and estimating the constant load cable rigidity K, and calculating the equivalent cable elastic modulus according to a catenary equation. Calculating live load influence line by using a finite element calculation method of a rod system structure according to the estimated constant load stay cable rigidity K, further calculating live load cable force, and obtaining recalculated live load maximum cable force F l ’。
Further according to the input initial constant load cable force F d And recalculated live load maximum cable force F l 'recalculating the cable specification omega', and then combining the initial constant load cable force F d Recalculating the stiffness K' of the stay cable, adopting a zero bending moment method, reducing the stiffness of the tower beam to p times in the finite element calculation of the rod system structure, wherein p is a positive value far less than 1 and can be 0.001, and recording the cable force of the stay cable at the moment, namely the final constant load cable force F obtained by recalculating d ’。
Finally, the initial dead load cable of the input and outputForce F d With recalculated live load maximum cable force F d ' the negative number of the second norm of the error, and the output value as the corresponding input constant load cable force F d The fitness of the sample. Where the second norm is the arithmetic square root of the sum of the squares of all the data.
The method and the device can estimate the initial constant-load cable force of the plurality of cables, further estimate the constant-load cable stiffness, recalculate the constant-load cable force according to the estimated constant-load cable stiffness to obtain the initial fitness of each individual, reasonably set the fitness function by evaluating the individuals, fully consider the nonlinear factors of the cable-stayed bridge with low calculation cost, and effectively increase the calculation efficiency.
Specifically, in one embodiment of the present application, the calculation formula of the initial live load cable force is:
wherein, F li Estimation of live load Cable force, Δ L, for the ith Cable i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc Concentrated load for live loads, theta i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
According to the formula, the live load cable force of each cable can be estimated according to the arrangement of the cables of the cable-stayed bridge, and the corresponding live load cable force estimated value is obtained.
Additionally, in one embodiment of the present application, calculating an estimated cable gauge from the initial deadweight cable force and the initial live load cable force includes: and calculating the specifications of the bridge-forming inhaul cables meeting the stress requirements according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle respectively to obtain the estimated inhaul cable specifications.
It can be understood that, in the embodiment of the application, the inhaul cable meeting the design requirements, namely meeting the safety coefficient index or the reliability index, can be selected according to the inhaul cable calculation method and the inhaul cable specification selection table which are set during the inhaul cable specification calculation, the steel inhaul cable can be controlled by adopting the safety coefficient, the carbon fiber composite inhaul cable can be controlled by adopting the reliability index, and then the calculation is performed according to the principle of presetting the maximum inhaul cable type quantity and presetting the minimum cable consumption. The mean value and the variation coefficient of the strength of the carbon fiber composite inhaul cable are obtained through deep learning prediction according to a unit strength index obtained through test data.
In the actual execution process, when the specification of the guy cable is recalculated according to the initial dead load cable force and the live load maximum cable force in calculating the initial fitness of each individual in the t-th generation population, the specification of the bridge-forming guy cable meeting the stress requirement can be calculated according to the preset maximum guy cable type quantity and the preset minimum cable consumption principle, and the recalculated guy cable specification is obtained.
It should be noted that the principle of presetting the maximum number of types of guy cables and presetting the minimum amount of guy cables is set by those skilled in the art according to actual situations, and is not specifically limited herein.
According to the method and the device, the bridge-forming inhaul cable specification meeting the stress requirement can be calculated according to the principle of presetting the maximum inhaul cable type quantity and the minimum inhaul cable quantity, so that the estimated inhaul cable specification is obtained, the data processing process of the genetic algorithm is further perfected, and the algorithm result is more accurate.
Specifically, in an embodiment of the present application, an expression of the predetermined least used amount rule is as follows:
wherein n is the number of the stay cables, L i The length of the i-th inhaul cable is N i I =1, 2, …, n for the ith cable number.
It can be understood that the number of cables and the scale of the cables in the embodiment of the application need to be within the total range of the stay cables, namely N i ∈Ω j ，j＝1、2，
Wherein omega j Is a set of the number of stay cables, omega 1 Is a set of the number of the steel stay cables, omega 1 The number of the elements is less than or equal to the set specification number P of the steel cable 1 ，Ω 2 Is a carbon fiber stayed cable root set, omega 2 The number of the elements is less than or equal to the set specification number P of the carbon fiber inhaul cable 2 。
According to the formula, the preset least cable consumption principle expression in the embodiment of the application can be used for calculating the specification of the bridge-forming inhaul cable meeting the stress requirement, so that an optimization processing mode is further provided for the operation of a genetic algorithm.
In step S103, based on the fitness of each individual in the population of the t-th generation, matching the probability of each individual being selected, applying a crossover operator to the population, and applying a mutation operator to the population until a preset iteration or a condition of terminating operation is reached, obtaining an individual with the highest fitness of the population, decoding the chromosome of the individual with the highest fitness, and obtaining an optimized numerical solution.
It is understood that, in the embodiment of the present application, a selection operation may be performed based on the fitness of each individual in the tth generation population obtained in the above steps, and the probability of each individual being selected is matched according to the fitness of each individual in the tth generation population P (t), and the individuals inherited to the next generation are randomly selected, so that the probability of the next generation inheritance of superior individuals is greater, for example, a roulette method may be selected, that is, the probability of each individual being selected is proportional to the fitness of the individual, thereby ensuring that the superior individuals have a greater probability of being selected. The crossover operator can determine the chromosome crossover position and crossover probability of each selected individual, and acts on the population through crossover operation. The mutation operator can determine the probability of mutation at different positions in each individual chromosome, and acts on the population through mutation operation.
In the actual iteration process of the genetic algorithm, if the maximum evolution algebra reaches T, terminating the evolution, outputting the individual with the highest fitness of the final population, and decoding the chromosome of the individual to obtain the design optimization numerical solution of the steel and carbon fiber hybrid cable-stayed bridge cable.
It should be noted that the preset iteration operation condition and the preset termination operation condition are set by those skilled in the art according to actual situations, and are not limited specifically herein.
In some embodiments, the genetic algorithm can be programmed, control language corresponding to the main structural design software is output to perform modeling calculation, the designer inputs necessary key geometric parameters and load parameters of cable-stayed bridge design to complete full-automatic design of cable specification and cable force, and the calculation error can meet the structural design requirement.
According to the embodiment of the application, based on the fitness of each individual in the t-th generation population, selection, crossing and variation operation can be sequentially carried out until a preset iteration or a termination operation condition is reached, the individual with the highest population fitness is obtained, the chromosome of the individual with the highest population is decoded, and an optimized numerical solution is obtained, so that the design process is optimized, the design efficiency is improved, and the application range of the design process is widened.
The operation of the embodiments of the present application will be described in detail below with reference to fig. 2-6.
Fig. 2 is a process diagram of a steel and carbon fiber hybrid cable-stayed bridge cable design method based on genetic algorithm and deep learning according to an embodiment of the present application.
In the design process of the steel and carbon fiber hybrid stay cable stayed bridge stay cable, firstly, initialization processing is carried out based on geometric parameters, load parameters, stay cable characteristics, the maximum variety number and a stay cable specification table, initial constant load cable force is input to further estimate live load cable force, estimated stay cable specifications are obtained, calculated live load cable force is obtained, the stay cable specifications are recalculated, the stay cable rigidity is recalculated, the constant load cable force is recalculated, fitness is calculated, selection operation, cross operation and variation operation are sequentially carried out, if the maximum evolution algebra i reaches T, the operation is stopped, and if the maximum evolution algebra i does not reach T, the loop operation is continued to execute an iterative process.
Through the above process, a reference cable-stayed bridge schematic as shown in fig. 3 can thus be obtained. Fig. 4 is a graph of an iterative calculation error of a reference cable-stayed bridge, fig. 5 is a line graph of safety coefficient and reliability index after the design of the reference cable-stayed bridge is completed, and fig. 6 is a line graph of cable force and cable specification before and after the cable iteration after the design of the reference cable-stayed bridge is completed, so as to further illustrate the design result of the cable of the steel and carbon fiber hybrid cable-stayed bridge.
According to the method for designing the stay cable of the steel and carbon fiber hybrid stay cable bridge, the basic geometric parameters and the basic load parameters of the cable-stayed bridge are determined, the stay cable characteristic data of the steel and carbon fiber hybrid stay cable, the maximum stay cable type quantity and the stay cable specification selection table of each type of stay cable are determined, optimization calculation is carried out based on a genetic algorithm and a deep learning mode, the fitness of each individual in the t generation group is obtained, calculation is carried out until preset iteration or calculation stopping conditions are reached, the individual with the highest fitness of the group is obtained, an optimized numerical solution is obtained, the estimation efficiency of the stay cable strength value is improved, the cable force calculation of the cable-stayed bridge can be more accurate, the automatic efficient design of the stay cable is further achieved, and the applicability is stronger. Therefore, the problems that in the related art, the non-linear degree of a steel and carbon fiber hybrid stay cable bridge is higher, the restraint is more, and in the hybrid arrangement, the rigidity difference between the stay cables which is larger than that of a single-material stay cable bridge is possibly generated, so that the difficulty of adjusting the stay cable force of the finished bridge is increased, the calculation efficiency of the design process of the stay cable of the cable-stayed bridge is reduced, and the fast and efficient design of the steel and carbon fiber hybrid stay cable bridge stay cable cannot be realized are solved.
Next, a steel and carbon fiber hybrid cable-stayed bridge cable design device provided according to an embodiment of the present application is described with reference to the accompanying drawings.
Fig. 7 is a block diagram of a cable design device of a hybrid steel and carbon fiber cable-stayed bridge according to an embodiment of the present application.
As shown in fig. 7, the steel and carbon fiber hybrid cable-stayed bridge cable design device 10 includes: a determination module 100, a calculation module 200 and an acquisition module 300.
The determining module 100 is configured to determine basic geometric parameters and basic load parameters of the cable-stayed bridge, and determine cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number of each type of cable, and a cable specification selection table.
And the calculation module 200 is used for performing optimization calculation according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable type quantity and the inhaul cable specification selection table based on the genetic algorithm and the deep learning mode to obtain the fitness of each individual in the population of the t generation, wherein t is a positive integer.
The obtaining module 300 is configured to match the probability of each individual being selected based on the fitness of each individual in the population of the t-th generation, apply a crossover operator to the population, apply a mutation operator to the population until a preset iteration or a condition of terminating operation is reached, obtain an individual with the highest fitness of the population, decode a chromosome of the individual with the highest fitness, and obtain an optimized numerical solution.
Optionally, in an embodiment of the present application, the computing module 200 includes: the device comprises a generating unit and a first calculating unit.
The generating unit is used for selecting the cable force within the preset range of the estimated cable force, forming an individual based on the cable forces of all the cables of the full bridge, enabling each individual to correspond to one chromosome, setting the maximum evolution algebra, and randomly generating a plurality of individuals as the initial population.
And the first calculating unit is used for calculating the initial fitness of each individual in the tth generation population.
Optionally, in an embodiment of the present application, the computing module 200 further includes: the device comprises a first estimation unit, a second calculation unit, a third calculation unit, a fourth calculation unit, a fifth calculation unit, a sixth calculation unit, a seventh calculation unit and an acquisition unit.
The first estimation unit is used for estimating initial constant load cable force of the plurality of stay cables according to the constant load.
And the second estimation unit is used for estimating the initial live load cable force according to the live load.
And the second calculation unit is used for calculating and estimating the specification of the inhaul cable according to the initial constant load cable force and the initial live load cable force.
And the third calculation unit is used for calculating and estimating the constant-load cable stiffness according to the initial constant-load cable force and the estimated cable specification.
And the fourth calculation unit is used for recalculating the live load maximum cable force according to the estimated constant load cable stiffness.
And the fifth calculating unit is used for recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live-load maximum cable force.
And the sixth calculating unit is used for calculating the rigidity of the inhaul cable according to the initial constant load cable force and the inhaul cable specification.
And the seventh calculating unit is used for recalculating the final constant-load cable force according to the constant load and the cable stiffness.
And the obtaining unit is used for obtaining the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
Optionally, in an embodiment of the present application, the calculation formula of the initial live load cable force is:
wherein, F li Estimation of live load Cable force, Δ L, for the ith Cable i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc Concentrated load for live loads, theta i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
Optionally, in an embodiment of the present application, the second calculating unit includes: and the bridge-forming inhaul cable specification calculation method is used for calculating the bridge-forming inhaul cable specification meeting the stress requirement according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle so as to obtain the estimated inhaul cable specification.
Optionally, in an embodiment of the present application, an expression of the predetermined least used amount rule is:
wherein n is the number of the stay cables, L i The length of the i-th inhaul cable is N i I =1, 2, …, n for the ith cable number.
It should be noted that the explanation of the embodiment of the method for designing a steel and carbon fiber hybrid cable-stayed bridge cable is also applicable to the device for designing a steel and carbon fiber hybrid cable-stayed bridge cable of the embodiment, and the details are not repeated herein.
According to the steel and carbon fiber hybrid cable-stayed bridge cable design device provided by the embodiment of the application, the basic geometric parameters and the basic load parameters of a cable-stayed bridge can be determined, the cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type quantity and the cable specification selection table of various types of cables are determined, optimization calculation is carried out based on a genetic algorithm and a deep learning mode, the fitness of each individual in the t generation group is obtained, calculation is carried out until preset iteration or calculation termination conditions are reached, the individual with the highest fitness of the group is obtained, an optimized numerical solution is obtained, the estimation efficiency of the cable strength value is improved, the cable force calculation of the cable-stayed bridge can be more accurate, the automatic efficient design of the cable is further realized, and the applicability is stronger. Therefore, the problems that in the related art, the non-linear degree of a steel and carbon fiber hybrid stay cable bridge is higher, the restraint is more, and in the hybrid arrangement, the rigidity difference between the stay cables which is larger than that of a single-material stay cable bridge is possibly generated, so that the difficulty of adjusting the stay cable force of the finished bridge is increased, the calculation efficiency of the design process of the stay cable of the cable-stayed bridge is reduced, and the fast and efficient design of the steel and carbon fiber hybrid stay cable bridge stay cable cannot be realized are solved.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 801, a processor 802, and a computer program stored on the memory 801 and executable on the processor 802.
The processor 802 executes the program to implement the method for designing the cable of the steel and carbon fiber hybrid cable-stayed bridge provided in the above embodiments.
Further, the electronic device further includes:
a communication interface 803 for communicating between the memory 801 and the processor 802.
A memory 801 for storing computer programs operable on the processor 802.
The memory 801 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 may be connected to each other via a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 8, but this is not intended to represent only one bus or type of bus.
Alternatively, in practical implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated into one chip, the memory 801, the processor 802 and the communication interface 803 may communicate with each other through an internal interface.
The processor 802 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steel and carbon fiber hybrid cable-stayed bridge cable design method as described above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a computer-readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (14)
1. A method for designing a steel and carbon fiber hybrid stay cable of a cable-stayed bridge is characterized by comprising the following steps:
determining basic geometric parameters and basic load parameters of the cable-stayed bridge, and determining cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number and cable specification selection table of various types of cables;
based on a genetic algorithm and a deep learning mode, carrying out optimization calculation according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable variety quantity and the inhaul cable specification selection table to obtain the fitness of each individual in the population of the t generation, wherein t is a positive integer; and
matching the selected probability of each individual based on the fitness of each individual in the population of the t generation, acting a crossover operator on the population, and acting a mutation operator on the population until a preset iteration or a termination operation condition is reached to obtain the individual with the highest fitness of the population, and decoding the chromosome of the highest individual to obtain an optimized numerical solution.
2. The method according to claim 1, wherein the optimizing calculation is performed according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable type quantity and the inhaul cable specification selection table based on a genetic algorithm and a deep learning mode to obtain the fitness of each individual in the tth generation population, and the method comprises the following steps:
selecting cable force within a preset range of estimated cable force, forming an individual based on the cable force of all full-bridge cables, enabling each individual to correspond to a chromosome, setting a maximum evolution algebra, and randomly generating a plurality of individuals as an initial population;
and calculating the initial fitness of each individual in the t-th generation population.
3. The method of claim 2, wherein calculating the initial fitness of each individual in the population of the t generation comprises:
estimating initial constant-load cable force of the plurality of stay cables according to the constant load;
estimating initial live load cable force according to the live load;
calculating and estimating the specification of the inhaul cable according to the initial constant-load cable force and the initial live-load cable force;
calculating and estimating the constant-load cable stiffness according to the initial constant-load cable force and the estimated cable specification;
recalculating the live load maximum cable force according to the estimated constant load cable stiffness;
recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live load maximum cable force;
calculating the rigidity of the stay cable according to the initial constant load cable force and the specification of the stay cable;
recalculating the final constant-load cable force according to the constant load and the cable rigidity;
and acquiring the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
4. The method of claim 3, wherein the initial live load cable force is calculated by the formula:
wherein, F li Estimation of live load Cable force, Δ L, for the ith Cable i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc As collections of live loadsMedium load, θ i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
5. The method of claim 4, wherein calculating an estimated guy rope specification from the initial deadweight cable force and the initial live weight cable force comprises:
and calculating the specifications of the bridge-forming inhaul cables meeting the stress requirements according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle respectively to obtain the estimated inhaul cable specifications.
6. The method of claim 5, wherein the expression of the predetermined least used metric is:
wherein n is the number of the stay cables, L i The length of the ith guy cable is N i I =1, 2, …, n for the ith cable number.
7. The utility model provides a steel and carbon fiber mix cable-stay bridge cable design device which characterized in that includes following step:
the determining module is used for determining basic geometric parameters and basic load parameters of the cable-stayed bridge, and determining cable characteristic data of the steel and carbon fiber hybrid cable, the maximum cable type number and cable specification selection table of various types of cables;
the calculation module is used for carrying out optimization calculation according to the basic geometric parameters, the basic load parameters, the inhaul cable characteristic data, the maximum inhaul cable type quantity and the inhaul cable specification selection table based on a genetic algorithm and a deep learning mode to obtain the fitness of each individual in the tth generation population, wherein t is a positive integer; and
and the acquisition module is used for matching the selected probability of each individual based on the fitness of each individual in the population of the t generation, acting a crossover operator on the population, acting a mutation operator on the population until a preset iteration or operation termination condition is reached, obtaining the individual with the highest fitness of the population, decoding the chromosome of the highest individual, and obtaining an optimized numerical solution.
8. The apparatus of claim 7, wherein the computing module comprises:
the generating unit is used for selecting and estimating the cable force within a preset range of the cable force, forming an individual based on the cable force of all full-bridge cables, enabling each individual to correspond to a chromosome, setting a maximum evolution algebra, and randomly generating a plurality of individuals as an initial population;
and the first calculating unit is used for calculating the initial fitness of each individual in the tth generation population.
9. The apparatus of claim 8, wherein the computing module further comprises:
the first estimation unit is used for estimating initial constant load cable force of the plurality of stay cables according to the constant load;
the second estimation unit is used for estimating the initial live load cable force according to the live load;
the second calculation unit is used for calculating and estimating the specification of the inhaul cable according to the initial constant-load cable force and the initial live-load cable force;
the third calculation unit is used for calculating and estimating the constant-load cable stiffness according to the initial constant-load cable force and the estimated cable specification;
the fourth calculation unit is used for recalculating the live load maximum cable force according to the estimated constant load cable stiffness;
the fifth calculation unit is used for recalculating the specification of the inhaul cable according to the initial constant-load cable force and the live-load maximum cable force;
the sixth calculating unit is used for calculating the rigidity of the inhaul cable according to the initial constant-load cable force and the inhaul cable specification;
the seventh calculating unit is used for recalculating the final constant load cable force according to the constant load and the cable rigidity;
and the obtaining unit is used for obtaining the initial fitness of each individual based on the negative number of the second norm of the error of the initial constant load cable force and the final constant load cable force.
10. The apparatus of claim 9, wherein the initial live load cable force is calculated by the formula:
wherein, F ii Estimation of live load Cable force, Δ L, for the ith Cable i The distance between the cables corresponding to the ith cable, F lu For live-loaded uniform distribution of load, F lc For concentrated loads of live loads, theta i Is the included angle between the ith cable and the horizontal plane, n is the number of the inhaul cables, and i =1, 2, …, n.
11. The apparatus of claim 10, wherein the second computing unit comprises: and calculating the specifications of the bridge-forming inhaul cables meeting the stress requirements according to the preset maximum inhaul cable type quantity and the preset minimum cable consumption principle respectively to obtain the estimated inhaul cable specifications.
12. The apparatus of claim 11, wherein the expression of the predetermined least used amount rule is:
wherein n is the number of the stay cables, L i The length of the i-th inhaul cable is N i I =1, 2, …, n for the ith cable number.
13. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the steel and carbon fiber hybrid cable-stayed bridge cable design method according to any of the claims 1-6.
14. A computer readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for implementing a steel and carbon fiber hybrid cable-stayed bridge cable design method according to any of the claims 1-6.
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| CN202211566919.8A CN115859434A (en) | 2022-12-07 | 2022-12-07 | Method and device for designing stay cable of steel and carbon fiber hybrid stay cable bridge |
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