CN113627103A - Laser fusion waveform and target structure optimization design method and device and computer equipment - Google Patents
Laser fusion waveform and target structure optimization design method and device and computer equipment Download PDFInfo
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Abstract
The application relates to a laser fusion waveform and target structure optimization design method, a device and computer equipment. The method comprises the following steps: acquiring initial parameters and initial parameter step lengths of a laser waveform and a target pill structure; generating a normalized random variable array corresponding to the initial parameters one by one; obtaining a new input parameter according to the initial parameter, the initial parameter step length and the normalized random variable array; writing the initial parameter step length into a radiation fluid mechanics program MULTI for calculation, comparing the calculation result with the calculation result corresponding to the initial parameter, and taking half of the initial parameter step length as a new parameter step length when the comparison result is greater than the initial parameter step length, otherwise, keeping the step length unchanged; and updating the initial parameters to new input parameters, updating the initial step length to a new parameter step length, and performing next round of optimization until a stopping condition is met to obtain a group of optimized parameters. The method is based on the radiation fluid mechanics program MULTII, can quickly find out proper parameters according to requirements, and is high in optimization efficiency and low in time cost.
Description
Technical Field
The application relates to the technical field of inertial confinement fusion, in particular to a laser fusion waveform and target structure optimization design method, a laser fusion waveform and target structure optimization design device and computer equipment.
Background
For solving the future energy, the controlled nuclear fusion which takes inexhaustible seawater as fuel and is characterized by high efficiency and cleanness is a research field hoped to be the greatest. Since the fifties of the 20 th century, developed countries and few developing countries in the world have invested a lot of manpower and material resources, and laser ignition devices with different sizes and scales, such as NIF and OMEGA in the united states, LMJ in france, VULCAN in england, SG series devices in China, etc., have been built in sequence. In 2006, an SG II upgrading system is built and put into operation, and the total energy output by 8 paths of lasers is 40KJ/3 omega/3 ns. For inertial confinement laser fusion, setting of laser waveform and target pellet structure parameters is very important, and the final result of the inertial confinement fusion is directly influenced. In one-dimensional simulation, a MULTI radiation hydrodynamics program is often used for simulation to search for appropriate parameters, although MULTI can be calculated quickly after parameters are input, in order to obtain a better result, dozens of or even more parameters need to be finely adjusted, the result is highly sensitive to the change of the input parameters, and due to the fact that the related parameters are too many, a corresponding rule is difficult to find, and the workload of manually and manually inputting the parameters to search for the inertial confinement fusion rule is very large.
Disclosure of Invention
In view of the above, there is a need to provide a method, an apparatus and a computer device for optimally designing laser fusion waveforms and target structures.
A method of laser fusion waveform and target structure optimization design, the method comprising:
and acquiring initial parameters and initial parameter step length of the laser waveform and the target pill structure, and taking the initial parameters as starting points of the first random walk.
And automatically generating a normalized random variable array corresponding to the initial parameters one by one.
And obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array.
And writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result.
And when the current surface density is less than or equal to the surface density corresponding to the initial parameter, taking the initial parameter step length as a new parameter step length, and when the current surface density is greater than the surface density corresponding to the initial parameter, taking half of the initial parameter step length as the new parameter step length.
And updating the initial parameter to a new input parameter, updating the initial step length to a new parameter step length, taking the new parameter step length as the starting point of the next random walk, and performing the next round of optimization calculation until the parameter step length is less than or equal to the minimum threshold value, and stopping the random walk to obtain a group of optimized parameters.
In one embodiment, obtaining new input parameters of the laser waveform and the target pellet structure according to the initial parameter, the initial parameter step size, and the normalized random variable array includes:
and multiplying the normalized random variable array by the initial parameter step length, and adding the initial parameter step length and the initial parameter step length to obtain new input parameters of the laser waveform and the target pill structure.
In one embodiment, the laser fusion waveforms optimized using the method include a plurality of laser waveforms.
In one embodiment, the target structure optimized using the method is: a single layer spherical target or a multi-layer spherical target.
In one embodiment, the method further includes the steps of updating an initial parameter to a new input parameter, updating the initial step size to a new parameter step size, using the new parameter step size as a starting point of next random walk, performing next round of optimization calculation, and stopping the random walk until the parameter step size is less than or equal to a minimum threshold value to obtain a set of optimized parameters, and after the steps:
and obtaining initial parameters and initial parameter step lengths of a plurality of groups of laser waveforms and target pellet structures, and repeating the steps of the laser fusion waveform and target structure optimization design method for a plurality of times to obtain a plurality of groups of optimized parameters.
And constructing a visual correlation matrix according to the plurality of groups of initial parameters and the corresponding optimized parameters to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
In one embodiment, constructing a visual correlation matrix according to the plurality of sets of initial parameters and the corresponding optimized parameters to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters includes:
and constructing a parameter matrix according to the plurality of groups of initial parameters and the corresponding optimization parameters.
And calculating by adopting a correlation matrix calculation formula according to the parameter matrix to obtain a correlation matrix.
And carrying out visual processing on the correlation matrix, and analyzing to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
A laser fusion waveform and target structure optimal design apparatus, the apparatus comprising:
and the initial data acquisition module is used for acquiring initial parameters and initial parameter step lengths of the laser waveform and the target pill structure, and taking the initial parameters as starting points of the first random walk.
The optimization calculation module is used for automatically generating a normalized random variable array which corresponds to the initial parameters one by one; obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array; writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result; and when the initial parameter step length is larger than a minimum threshold value, taking the initial parameter step length as a new parameter step length when the current surface density is smaller than or equal to the surface density corresponding to the initial parameter, and taking half of the initial parameter step length as the new parameter step length when the current surface density is larger than the surface density corresponding to the initial parameter.
And the optimization parameter determining module is used for updating the initial parameters to new input parameters, taking the new input parameters as the starting point of the next random walk, and performing the next round of optimization calculation until the random walk stops when the parameter step length is less than or equal to the minimum threshold value to obtain a group of optimization parameters.
The laser fusion waveform and target structure optimization design method, device and computer equipment comprise the following steps: acquiring initial parameters and initial parameter step length of a laser waveform and a target pill structure, and taking the initial parameters as starting points of first random walk; automatically generating a normalized random variable array corresponding to the initial parameters one by one; obtaining a new input parameter according to the initial parameter, the initial parameter step length and the normalized random variable array; writing the initial parameter step length into a radiation fluid mechanics program MULTI for calculation, comparing the obtained calculation result with the calculation result corresponding to the initial parameter, and taking half of the initial parameter step length as a new parameter step length when the comparison result is greater than the initial parameter step length, otherwise, keeping the step length unchanged; and updating the initial parameters to new input parameters, updating the initial step length to a new parameter step length, taking the new parameter step length as the starting point of the next random walk, and performing the next round of optimization calculation until the parameter step length is less than or equal to the minimum threshold value, and stopping the random walk to obtain a group of optimized parameters. The method is based on the radiation fluid mechanics program MULTII, can quickly find out proper parameters according to requirements, and has the advantages of high efficiency and low time cost.
Drawings
FIG. 1 is a schematic flow diagram of a method for optimal design of laser fusion waveforms and target structures in one embodiment;
FIG. 2 is a schematic flow chart of a laser fusion waveform and target structure optimization design method in another embodiment;
FIG. 3 is a block diagram of an apparatus for optimally designing laser fusion waveforms and target structures in one embodiment;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in FIG. 1, there is provided a laser fusion waveform and target structure optimization design method, comprising the steps of:
step 100: and acquiring initial parameters and initial parameter step length of the laser waveform and the target pill structure, and taking the initial parameters as starting points of the first random walk.
The initial parameters include: to determine sets of power-time coordinates of the laser waveform to describe the inner radius of the target structure and the thickness of each outer layer.
The initial parameter step size is the minimum unit of each parameter change in the parameter optimization process, each parameter corresponds to a specific step size, and the step size is gradually reduced in the optimization process.
Step 102: and automatically generating a normalized random variable array corresponding to the initial parameters one by one.
The normalized random variable array is randomly generated and has the same dimensions as the initial parameters.
The normalization random array is used for generating new parameters and randomly disturbing each parameter within a certain range, and the normalization is used for preventing the parameter disturbance from exceeding the range too much.
Step 104: and obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array.
Step 106: and writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result.
Step 108: and when the current surface density is less than or equal to the surface density corresponding to the initial parameter, taking the initial parameter step length as a new parameter step length, and when the current surface density is greater than the surface density corresponding to the initial parameter, taking half of the initial parameter step length as the new parameter step length.
The minimum threshold is a preset termination condition for loop parameter optimization, and is the minimum value of the parameter step size.
Step 110: and updating the initial parameters to new input parameters, updating the initial step length to a new parameter step length, taking the new parameter step length as the starting point of the next random walk, and performing the next round of optimization calculation until the parameter step length is less than or equal to the minimum threshold value, and stopping the random walk to obtain a group of optimized parameters.
In the above method for optimally designing the laser fusion waveform and the target structure, the method comprises the following steps: acquiring initial parameters and initial parameter step length of a laser waveform and a target pill structure, and taking the initial parameters as starting points of first random walk; automatically generating a normalized random variable array corresponding to the initial parameters one by one; obtaining a new input parameter according to the initial parameter, the initial parameter step length and the normalized random variable array; writing the initial parameter step length into a radiation fluid mechanics program MULTI for calculation, comparing the obtained calculation result with the calculation result corresponding to the initial parameter, and taking half of the initial parameter step length as a new parameter step length when the comparison result is greater than the initial parameter step length, otherwise, keeping the step length unchanged; and updating the initial parameters to new input parameters, updating the initial step length to a new parameter step length, taking the new parameter step length as the starting point of the next random walk, and performing the next round of optimization calculation until the parameter step length is less than or equal to the minimum threshold value, and stopping the random walk to obtain a group of optimized parameters. The method is based on the radiation fluid mechanics program MULTII, can quickly find out proper parameters according to requirements, and has the advantages of high efficiency and low time cost.
In one embodiment, step 104 further comprises: and multiplying the normalized random variable array by the initial parameter step length, and adding the initial parameter step length and the initial parameter step length to obtain new input parameters of the laser waveform and the target pill structure.
In one embodiment, the laser fusion waveforms optimized using the method include a plurality of laser waveforms. Preferably, the method comprises the following steps: the laser waveform may be a platform wave or a ramp wave.
In one embodiment, the target structure optimized using the method is: a single layer spherical target or a multi-layer spherical target.
In one embodiment, step 110 is followed by:
step 201: acquiring initial parameters and initial parameter step lengths of a plurality of groups of laser waveforms and target pill structures, and repeating the steps in the method of claim 1 for a plurality of times to obtain a plurality of groups of optimized parameters.
Step 202: and constructing a visual correlation matrix according to the plurality of groups of initial parameters and the corresponding optimized parameters to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
In one embodiment, step 202 further comprises:
and constructing a parameter matrix according to the plurality of groups of initial parameters and the corresponding optimization parameters.
And calculating by adopting a correlation matrix calculation formula according to the parameter matrix to obtain a correlation matrix.
And carrying out visual processing on the correlation matrix, and analyzing to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
In one embodiment, as shown in fig. 2, a method for optimizing laser fusion waveform and target structure parameters based on the random walk principle is provided, the method includes automatically generating normalized random arrays corresponding to the parameters one by one, multiplying the corresponding arrays by the step length in different step lengths corresponding to different kinds of parameters, and adding the multiplied arrays to the original parameters to obtain a new set of input parameters.
And further writing the obtained new input parameters into a parameter input file of the MULTI, calculating to obtain a calculation result, and comparing the calculation result with a result corresponding to the original parameters.
Further, a new set of parameters will replace the original parameters as the starting point for the next random walk.
Further, if the result corresponding to the new group of parameters is better than the result corresponding to the original parameters, the step length corresponding to each parameter is changed to be half of the original step length, otherwise, the step length is kept unchanged, the first step is repeated to obtain a new plurality of groups of parameters, and the new group of parameters are input into the MULTI and are continuously repeated.
Further, when the step size is smaller than the minimum threshold, the optimization parameters are output.
Further, the steps are repeated for multiple times, and more sets of optimization parameters are obtained.
And further, constructing a correlation matrix according to the multiple groups of optimization parameters to obtain the correlation between each input parameter and the optimization parameters.
In another embodiment, a method for optimizing laser fusion waveform and target structure parameters based on random walk principle comprises: automatically generating a normalized random array corresponding to the parameters one by one, different step lengths corresponding to different kinds of parameters, multiplying the corresponding array by the step length, adding the multiplied array to the original parameters to obtain a group of new input parameters, repeating the step for multiple times, and obtaining multiple groups of new parameters based on the same group of original parameters.
Furthermore, writing the obtained multiple groups of parameters into a parameter input file of the MULTI, respectively calculating corresponding results, and selecting one group of the multiple groups of parameters with the best result to compare with the result corresponding to the original parameter.
Further, a new set of parameters will replace the original parameters as the starting point for the next random walk.
Further, if the result corresponding to the new group of parameters is better than the result corresponding to the original parameters, the step length corresponding to each parameter is changed to be half of the original step length, otherwise, the step length is kept unchanged, the first step is repeated to obtain a new plurality of groups of parameters, and the new group of parameters are input into the MULTI and are continuously repeated.
And further, when the step length is smaller than the minimum threshold, outputting the current result to obtain a result extreme value.
Further, the steps are repeated for a plurality of times, and more sets of polar data are obtained, wherein the maximum values are included.
Furthermore, a correlation matrix is constructed by a plurality of sets of extreme value data, and the correlation between each input parameter and the result parameter is obtained.
In this embodiment, a plurality of sets of new parameters are calculated first, only to simply scan the surrounding area with the original parameter as the center, and only the set with the largest area density among the plurality of sets of new parameters is selected to be compared with the area density corresponding to the original parameter. The function can be switched off, further reducing the time cost; and the method can also be started to reduce the influence caused by the randomness of the parameters.
Compared with the prior art, the method has the following beneficial effects:
1. according to the invention, each parameter does not need to be manually adjusted, and automatic optimization can be rapidly carried out after a laser waveform parameter with a similar total pulse width is input, so that the efficiency is higher;
2. because the step length which is gradually reduced along with the result is introduced in the random walk process, the efficiency is higher, and the input parameters corresponding to the extreme value of the result can be found out quickly;
3. because the optimization speed is high, hundreds of groups of optimized input parameters and result parameters can be calculated in a short time, a correlation matrix can be constructed, and the relationship among all the parameters can be better analyzed;
it should be understood that although the various steps in the flow charts of fig. 1-2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In a specific embodiment of the laser fusion waveform and target structure optimization design method, Matlab is adopted to generate new random parameters, a python program is used for writing into an input file fort12 of the MULTII, Matlab calls an executable program in the MULTII to perform simulation calculation, Matlab is used for reading a result storage file fort10 of the MULTII, surface density is calculated, comparison with a previous result is performed, the size of the surface density is compared, the step size of the random parameters is shortened or kept, a next group of new random parameters are generated, next round of calculation is performed until the step size of the parameters is small enough, and the latest input parameters are output.
And after obtaining a plurality of groups of input parameters which can obtain a maximum value result, constructing a visual correlation matrix and analyzing the correlation among the parameters.
In one embodiment, as shown in fig. 3, there is provided a laser fusion waveform and target structure optimization design apparatus, comprising: the device comprises an initial data acquisition module, an optimization calculation module and an optimization parameter determination module, wherein:
and the initial data acquisition module is used for acquiring initial parameters of the laser waveform and the target pill structure and initial parameter step length, and taking the initial parameters as the starting points of the first random walk.
The optimization calculation module is used for automatically generating a normalized random variable array which corresponds to the initial parameters one by one; obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array; writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result; and when the current surface density is less than or equal to the surface density corresponding to the initial parameter, taking the initial parameter step length as a new parameter step length, and when the current surface density is greater than the surface density corresponding to the initial parameter, taking half of the initial parameter step length as the new parameter step length.
And the optimization parameter determining module is used for updating the initial parameters to new input parameters, taking the new input parameters as the starting point of the next random walk, and performing the next round of optimization calculation until the random walk stops when the parameter step length is less than or equal to the minimum threshold value to obtain a group of optimization parameters.
In one embodiment, the optimization calculation module is further configured to multiply the normalized random variable array by the initial parameter step size, and add the multiplied value to the initial parameter to obtain new input parameters of the laser waveform and the target pellet structure.
In one embodiment, the optimization calculation module is further configured to multiply the normalized random variable array by the initial parameter step size, and add the multiplied value to the initial parameter to obtain new input parameters of the laser waveform and the target pellet structure.
In one embodiment, the laser fusion waveforms that can be optimized using the device include a variety of laser waveforms. The laser waveform may be a platform wave or a ramp wave as preferred.
In one embodiment, the target structure that can be optimized using the apparatus is: a single layer spherical target or a multi-layer spherical target.
In one embodiment, the optimization parameter determination module further includes: and a parameter correlation analysis module. The parameter correlation analysis module is used for acquiring initial parameters and initial parameter step lengths of a plurality of groups of laser waveforms and target pellet structures, and repeating the steps of the laser fusion waveform and target structure optimization design method for a plurality of times to obtain a plurality of groups of optimized parameters; and constructing a visual correlation matrix according to the plurality of groups of initial parameters and the corresponding optimized parameters to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
In one embodiment, the parameter correlation analysis module is further configured to construct a parameter matrix according to the multiple sets of initial parameters and the corresponding optimization parameters; calculating by adopting a correlation matrix calculation formula according to the parameter matrix to obtain a correlation matrix; and carrying out visual processing on the correlation matrix, and analyzing to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
For specific definition of the laser fusion waveform and target structure optimization design device, reference can be made to the above definition of the laser fusion waveform and target structure optimization design method, and details are not repeated here. The modules in the laser fusion waveform and target structure optimization design device can be completely or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a laser fusion waveform and target structure optimization design method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In an embodiment, a computer device is provided, comprising a memory storing a computer program and a processor implementing the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for optimally designing laser fusion waveforms and target structures, comprising the steps of:
acquiring initial parameters and initial parameter step length of a laser waveform and a target pill structure, and taking the initial parameters as starting points of first random walk;
automatically generating a normalized random variable array corresponding to the initial parameters one by one;
obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array;
writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result;
when the current surface density is less than or equal to the surface density corresponding to the initial parameter, taking the initial parameter step length as a new parameter step length, and when the current surface density is greater than the surface density corresponding to the initial parameter, taking half of the initial parameter step length as the new parameter step length;
and updating the initial parameter to a new input parameter, updating the initial step length to a new parameter step length, taking the new parameter step length as the starting point of the next random walk, and performing the next round of optimization calculation until the parameter step length is less than or equal to the minimum threshold value, and stopping the random walk to obtain a group of optimized parameters.
2. The method of claim 1, wherein deriving new input parameters for the laser waveform and the target pellet structure from the initial parameters, the initial parameter step size, and the normalized random variable array comprises:
and multiplying the normalized random variable array by the initial parameter step length, and adding the initial parameter step length and the initial parameter step length to obtain new input parameters of the laser waveform and the target pill structure.
3. The method of claim 1, wherein said method optimized laser fusion waveforms comprise a plurality of laser waveforms.
4. The method of claim 1, wherein the target structure optimized using the method is: a single layer spherical target or a multi-layer spherical target.
5. The method according to claim 1, wherein the initial parameter is updated to a new input parameter, the initial step size is updated to a new parameter step size, the new parameter step size is used as a starting point of a next random walk, a next round of optimization calculation is performed, and the random walk is stopped until the parameter step size is less than or equal to a minimum threshold value, so as to obtain a set of optimized parameters, and the method further comprises the following steps:
acquiring initial parameters and initial parameter step lengths of a plurality of groups of laser waveforms and target pill structures, and repeating the steps in the method of claim 1 for a plurality of times to obtain a plurality of groups of optimized parameters;
and constructing a visual correlation matrix according to the plurality of groups of initial parameters and the corresponding optimized parameters to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
6. The method of claim 5, wherein constructing a visual correlation matrix from the plurality of sets of initial parameters and corresponding optimized parameters to obtain relationships between different laser waveform parameters, target pellet structure parameters, and fusion result parameters comprises:
constructing a parameter matrix according to the plurality of groups of initial parameters and the corresponding optimization parameters;
calculating by adopting a correlation matrix calculation formula according to the parameter matrix to obtain a correlation matrix;
and carrying out visual processing on the correlation matrix, and analyzing to obtain the relationship among different laser waveform parameters, target pellet structure parameters and fusion result parameters.
7. A laser fusion waveform and target structure optimal design apparatus, comprising:
the initial data acquisition module is used for acquiring initial parameters and initial parameter step lengths of the laser waveform and the target pill structure, and taking the initial parameters as starting points of first random walk;
the optimization calculation module is used for automatically generating a normalized random variable array which corresponds to the initial parameters one by one; obtaining new input parameters of the laser waveform and the target pill structure according to the initial parameters, the initial parameter step length and the normalized random variable array; writing the new input parameters into a radiation fluid mechanics program MULTI for calculation, and obtaining the current surface density according to the calculation result; when the initial parameter step length is larger than a minimum threshold value, when the current surface density is larger than the surface density corresponding to the initial parameter, taking half of the initial parameter step length as a new parameter step length, and when the current surface density is smaller than or equal to the surface density corresponding to the initial parameter, the step length is unchanged;
and the optimization parameter determining module is used for updating the initial parameters to new input parameters, taking the new input parameters as the starting point of the next random walk, and performing the next round of optimization calculation until the random walk stops when the parameter step length is less than or equal to the minimum threshold value to obtain a group of optimization parameters.
8. The apparatus of claim 7, wherein the optimization calculation module is further configured to multiply the normalized random variable array by the initial parameter step size, and add the multiplied value to the initial parameter to obtain new input parameters of the laser waveform and the target structure.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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