Complex optimization design problem-oriented sample point evaluation process parallelization method

Abstract

The invention discloses a sample point evaluation process parallelization method for a complex optimization design problem, and belongs to the technical field of aerodynamic configuration design of aircrafts. In order to improve the multi-disciplinary performance evaluation efficiency and the multi-disciplinary optimization design efficiency of the aircraft, the method comprises the steps that a multi-disciplinary sample point evaluation flow chart is drawn, and the chart comprises all disciplinary relations; representing a single sample point evaluation process as a sub-process set; for the sub-process set, determining hierarchies from left to right, setting the hierarchies of the sub-processes at the leftmost end as the first hierarchies, and performing hierarchies labeling on each sub-process according to a sequence from left to right based on a branch hierarchies increasing mode; creating a hierarchical task pool of each hierarchy, and decomposing all sample evaluation processes into a plurality of irrelevant parallel task pools classified according to the hierarchy; and completing the parallel evaluation process of the serial sample points of the hierarchical task pools one by one according to a hierarchical sequence, and calculating the evaluation efficiency of a single sample point. According to the method, the multi-disciplinary performance evaluation efficiency and the multi-disciplinary optimization design efficiency of the aircraft can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of aircraft aerodynamic shape design, and in particular relates to a sample point evaluation process parallelization method for complex optimization design problems. Background Art

[0002] Modern aircraft aerodynamic shape design primarily combines computational fluid dynamics (CFD) and numerical optimization techniques, using computers to automatically find the optimal aerodynamic shape that meets performance requirements. With the advancement of aircraft design technology, aircraft aerodynamic shape design has evolved from solely considering aerodynamic performance to a complex system design problem that takes aerodynamics as the core and comprehensively considers the constraints and performance of disciplines such as structure, control, and flight mechanics.

[0003] During multidisciplinary optimization design, the optimization algorithm repeatedly generates multiple aircraft aerodynamic shapes and numerically analyzes the performance of each discipline to determine the optimization path and ultimately find the optimal aircraft aerodynamic shape. In multidisciplinary optimization design, the process of generating the aircraft aerodynamic shape and evaluating its performance in each discipline is a single-sample-point evaluation process.

[0004] When faced with complex optimization design problems, the sample point evaluation process involves the performance evaluation of multiple disciplines, with data reuse between disciplines. The logical sequence of the evaluation process is complex, making it a complex sample point evaluation process compared to a single-discipline optimization design process. The current optimization design process often uses a serial method for sample point evaluation, that is, using one or more CPU cores to sequentially evaluate the performance of all disciplines at a single sample point. Although this method reduces system complexity, it does not consider the relationship between disciplines. If there is no interaction between disciplines, it is still necessary to wait for the evaluation of other disciplines before conducting an evaluation. This method results in a waste of computer computing resources, reduces the efficiency of the aircraft's multi-disciplinary performance evaluation, and further reduces the efficiency of the overall aircraft aerodynamic shape optimization design. Summary of the Invention

[0005] The problem to be solved by the present invention is to improve the efficiency of multidisciplinary performance evaluation and multidisciplinary optimization design of aircraft, and propose a parallelization method for sample point evaluation process for complex optimization design problems.

[0006] To achieve the above object, the present invention is implemented through the following technical solutions:

[0007] A parallelized method for sample point evaluation process for complex optimization design problems includes the following steps:

[0008] S1. Draw a multidisciplinary sample site assessment flow chart, including the relationships between disciplines;

[0009] S2. Based on the multidisciplinary sample point evaluation flowchart obtained in step S1, the single sample point evaluation process is represented as a set of sub-processes;

[0010] S3. For the sub-process set obtained in step S2, determine the hierarchy from left to right, set the hierarchy of the leftmost sub-process to the first level, and label each sub-process with a hierarchy based on the increasing branch hierarchy from left to right;

[0011] S4. Create a hierarchical task pool for each level, decomposing all sample evaluation processes into multiple unrelated parallelizable task pools classified by level;

[0012] S5. Complete the parallel evaluation process of serial sample points of each hierarchical task pool one by one in hierarchical order, and calculate the evaluation efficiency of a single sample point.

[0013] Furthermore, the multidisciplinary sample point evaluation in step S1 includes one or a combination of aerodynamic performance evaluation, structural performance evaluation, control performance evaluation, and flight mechanics performance evaluation.

[0014] Furthermore, step S2 represents the single sample point evaluation process as a set of sub-processes, which is expressed as follows:

[0015]

[0016] Among them, P is the set of sub-processes, is the i-th subprocess.

[0017] Furthermore, the specific implementation method of step S3 is to hierarchically label the sub-process set P, and set the sub-process to contain three states, namely no pre-dependency, pre-dependency and the number of pre-dependencies is 1, and pre-dependency and the number of pre-dependencies is greater than 1. The expression is:

[0018]

[0019] in, for level, express The set of all predecessor subprocesses of express The number of elements in the set of all predecessor subprocesses, To find the maximum value.

[0020] Furthermore, the method for creating a hierarchical task pool for each level in step S4 is to set a level identifier set , sample set , number of layers , hierarchical task pool , then the expression of the stratification process is:

[0021]

[0022] in, For the Layer task pool, For the samples, The current layer number.

[0023] Furthermore, in step S5, the single sample point evaluation efficiency is calculated The calculation formula is:

[0024]

[0025] in, represents the serial evaluation time, represents the parallel evaluation time, express The execution time, For the Layer task pool.

[0026] Beneficial effects of the present invention:

[0027] The present invention describes a parallelization method for sample point evaluation processes in complex optimization design problems. By considering the multidisciplinary evaluation relationships within the samples, the serial process is parallelized, improving the efficiency of multidisciplinary performance evaluation and multidisciplinary optimization design for aircraft. This method, when applied to the multidisciplinary optimization design process for aircraft, can improve the efficiency of multidisciplinary performance evaluation and multidisciplinary optimization design. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of a parallelization method for sample point evaluation process for complex optimization design problems according to the present invention;

[0029] Figure 2 A schematic diagram of multidisciplinary relationships and evaluation processes in the multidisciplinary optimization design process of the present invention;

[0030] Figure 3 This is a schematic diagram of the hierarchical identification of each sub-process in the evaluation process of the present invention. DETAILED DESCRIPTION

[0031] In order to make the objectives, technical solutions, and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present invention and are not intended to limit the present invention. That is, the specific embodiments described herein are only some embodiments of the present invention, not all embodiments. Generally, the components of the specific embodiments of the present invention described and illustrated in the drawings herein can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0032] Therefore, the following detailed description of the specific embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected specific embodiments of the present invention. All other specific embodiments obtained by those skilled in the art based on the specific embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0033] In order to further understand the content, features and effects of the present invention, the following specific embodiments are given as examples, and the attached Figure 1 -Attached Figure 3 The detailed instructions are as follows:

[0034] Example 1:

[0035] A parallelized method for sample point evaluation process for complex optimization design problems includes the following steps:

[0036] S1. Draw a multidisciplinary sample site assessment flow chart, including the relationships between disciplines;

[0037] Furthermore, the multidisciplinary sample point evaluation in step S1 includes one or a combination of aerodynamic performance evaluation, structural performance evaluation, control performance evaluation, and flight mechanics performance evaluation;

[0038] S2. Based on the multidisciplinary sample point evaluation flowchart obtained in step S1, the single sample point evaluation process is represented as a set of sub-processes;

[0039] Furthermore, step S2 represents the single sample point evaluation process as a set of sub-processes, which is expressed as follows:

[0040]

[0041] Among them, P is the set of sub-processes, is the i-th subprocess;

[0042] S3. For the sub-process set obtained in step S2, determine the hierarchy from left to right, set the hierarchy of the leftmost sub-process to the first level, and label each sub-process with a hierarchy based on the increasing branch hierarchy from left to right;

[0043] Furthermore, the specific implementation method of step S3 is to hierarchically label the sub-process set P, and set the sub-process to contain three states, namely no pre-dependency, pre-dependency and the number of pre-dependencies is 1, and pre-dependency and the number of pre-dependencies is greater than 1. The expression is:

[0044]

[0045] in, for level, express The set of all predecessor subprocesses of express The number of elements in the set of all predecessor subprocesses, To find the maximum value.

[0046] S4. Create a hierarchical task pool for each level, decomposing all sample evaluation processes into multiple unrelated parallelizable task pools classified by level;

[0047] Furthermore, the method for creating a hierarchical task pool for each level in step S4 is to set a level identifier set , sample set , number of layers , hierarchical task pool , then the expression of the stratification process is:

[0048]

[0049] in, For the Layer task pool, For the samples, The current layer number.

[0050] S5. Complete the parallel evaluation process of serial sample points of each hierarchical task pool one by one in hierarchical order, and calculate the evaluation efficiency of a single sample point.

[0051] Furthermore, in step S5, the single sample point evaluation efficiency is calculated The calculation formula is:

[0052]

[0053] in, represents the serial evaluation time, represents the parallel evaluation time, express The execution time, For the Layer task pool.

[0054] This embodiment is put into practical application as Figure 2 As shown, first set the level of the leftmost terminal process to Lev_1, such as Figure 2 As shown in the ① sub-process;

[0055] Assign values ​​to each sub-process from left to right. If a branch is encountered, the branch level increases, such as Figure 2 From ① to ② and ③, the level of ① is Lev_1, and the levels of ② and ③ are Lev_2;

[0056] The case without branches is at the same level, such as Figure 2 In ④ and ⑤, these two sub-processes are combined during the evaluation. It should be noted that the same level without a connection relationship cannot be combined.

[0057] For a sub-process where multiple branches converge, the maximum value of all connected levels + 1 is taken as the level of the sub-process, such as Figure 2 As shown in the ⑧ component, the level of the ⑧ component is the maximum value among ⑤⑥⑦ + 1, which is Lev_5.

[0058] Then, build task pools at different levels such as Figure 3 As shown in the figure, there are five task pools, levels 1 to 5. Tasks within task pools at the same level are independent of each other and can be completed in parallel. All tasks within each task pool are completed sequentially and in parallel, completing multidisciplinary performance evaluations across multiple sample evaluation processes and across unrelated disciplines within a single sample evaluation process. The process of constructing task pools at different levels is to aggregate the to-be-evaluated processes of different sample points with the same level identifier to form a set of to-be-evaluated processes at that level. Each process in the set has two identifiers: the level identifier and the sample sequence identifier.

[0059] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

[0060] Although the present application has been described above with reference to specific embodiments, various modifications may be made thereto and components may be substituted with equivalents without departing from the scope of the present application. In particular, as long as there are no structural conflicts, the various features of the embodiments disclosed herein may be combined with each other in any manner, and the omission of an exhaustive description of these combinations in this specification is solely for the sake of space and resource conservation. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions within the scope of the claims.

Claims

1. A parallelization method for sample point evaluation process for complex optimization design problems, characterized by: The steps include: S1. Draw a multidisciplinary sample site assessment flow chart, including the relationships between disciplines; S2. Based on the multidisciplinary sample point evaluation flowchart obtained in step S1, the single sample point evaluation process is represented as a set of sub-processes; S3. For the sub-process set obtained in step S2, determine the hierarchy from left to right, set the hierarchy of the leftmost sub-process to the first level, and label each sub-process with a hierarchy based on the increasing branch hierarchy from left to right; S4. Create a hierarchical task pool for each level, decomposing all sample evaluation processes into multiple unrelated parallelizable task pools classified by level; S5. Complete the parallel evaluation process of serial sample points of each hierarchical task pool one by one in hierarchical order, and calculate the evaluation efficiency of a single sample point.

2. The method for parallelizing the sample point evaluation process for complex optimization design problems according to claim 1, characterized in that: The multidisciplinary sample point evaluation in step S1 includes one or a combination of aerodynamic performance evaluation, structural performance evaluation, control performance evaluation, and flight mechanics performance evaluation.

3. A parallelization method for sample point evaluation process for complex optimization design problems according to claim 1 or 2, characterized in that: Step S2 represents the single sample point evaluation process as a set of sub-processes, expressed as: Among them, P is the set of sub-processes, is the i-th subprocess.

4. The method for parallelizing the sample point evaluation process for complex optimization design problems according to claim 3, characterized in that: The specific implementation method of step S3 is to hierarchically label the sub-process set P and set the sub-process to contain three states: no pre-dependency, pre-dependency exists and the number of pre-dependencies is 1, and pre-dependency exists and the number of pre-dependencies is greater than 1. The expression is: in, for level, express The set of all predecessor subprocesses of express The number of elements in the set of all predecessor subprocesses, To find the maximum value.

5. The method for parallelizing the sample point evaluation process for complex optimization design problems according to claim 4, characterized in that: The method for creating a hierarchical task pool for each level in step S4 is to set the level identifier set , sample set , number of layers , hierarchical task pool , then the expression of the stratification process is: in, For the Layer task pool, For the samples, The current layer number.

6. The method for parallelizing the sample point evaluation process for complex optimization design problems according to claim 5, characterized in that: In step S5, the single sample point evaluation efficiency is calculated The calculation formula is: in, represents the serial evaluation time, represents the parallel evaluation time, express The execution time, For the Layer task pool.

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