Quantitative evaluation method for the wake effect of a powered parachute on a high-altitude parachute ladder wind-catching device

Abstract

The present invention discloses a quantitative evaluation method for the wake impact of a working parachute on a high-altitude parachute ladder wind-catching device, comprising: S1, data preparation: according to the typical operating conditions of the parachute ladder, a three-dimensional sample data set is obtained through CFD simulation collection; S2, wake impact modeling: according to the three-dimensional sample data set, a symbolic regression method is used to establish an evaluation model for the wake impact of the working parachute; S3, quantitative evaluation: the evaluation model for the wake impact of the working parachute is used to quantitatively evaluate the wake impact of the working parachute. The present invention is aimed at a land-based high-altitude parachute ladder wind-catching device, based on the symbolic regression method and CFD simulation, and takes the degree of recovery of the flow velocity behind the working parachute as a quantitative standard, so that only a small amount of CFD simulation experimental data is required to guide the quantifiable design of the spacing between the working parachutes of the parachute ladder.

Description

Technical Field

[0001] The present application relates to the field of land-based parachute ladder type high-altitude wind energy capture, and in particular to a quantitative evaluation method for the wake impact of a working parachute behind a high-altitude parachute ladder wind capture device. Background Art

[0002] Land-based high-altitude parachute ladder wind energy capture technology is a high-altitude wind energy capture method that connects a parachute ladder consisting of a row of working parachutes (drag parachutes) to ground equipment through traction cables. The aerodynamic force obtained by the working parachutes in the wind is used to pull the ropes to generate traction along the direction of the ropes. The traction force is converted through some transmission devices to drive the generator set to rotate, and the work done by the traction force to stretch the rope is converted into electrical energy.

[0003] Since the power parachute has a blunt body shape and has a large flow separation, the wake generated will have an adverse effect on the aerodynamic performance of the rear parachute, thereby reducing the wind-catching ability of the parachute ladder. In the design process of the parachute ladder, in order to reduce the adverse effects of the above wake, a larger power parachute spacing will be set to dissipate the wake generated by the previous power parachute as much as possible, in order to reduce the impact of the wake on the aerodynamic performance of the rear parachute. However, there is currently no quantitative standard or method to guide the design of the power parachute spacing scheme for the parachute ladder system. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a quantitative evaluation method for the influence of the wake behind the working parachute on the high-altitude parachute ladder wind-catching device. For the land-based high-altitude parachute ladder wind-catching device, based on the symbolic regression method and CFD simulation, the degree of recovery of the flow velocity behind the working parachute is taken as the quantitative standard. Only a small amount of CFD simulation experimental data is needed to guide the quantifiable design of the spacing between the working parachutes of the parachute ladder.

[0005] In order to achieve the above-mentioned invention object, the technical solution adopted by the present invention is: a quantitative evaluation method for the wake influence of a working parachute behind a high-altitude parachute ladder wind-catching device, comprising:

[0006] S1. Data preparation: According to the typical operating conditions of the parachute ladder, a three-dimensional sample data set is obtained through CFD simulation;

[0007] S2. Wake impact modeling: Based on the three-dimensional sample data set, the symbolic regression method is used to establish an evaluation model for the wake impact behind the power parachute;

[0008] S3. Quantitative evaluation: The wake impact behind a power parachute is quantitatively evaluated using an evaluation model for the wake impact behind a power parachute.

[0009] Further: S1 includes:

[0010] S11. Based on the operating height range of the parachute ladder and the wind field conditions, determine the wind speed range and density range of the working parachute at the position of the parachute during the operation of the parachute ladder, as well as the inclination range of the parachute ladder operation;

[0011] S12, selecting wind speed V, ladder inclination angle β, and density ρ within the interval, and combining the obtained groups (V, β, ρ) as input parameters for each CFD working condition;

[0012] S13, according to the CFD input parameters of each working condition, using CFD simulation to obtain the flow field velocity data behind a single working parachute;

[0013] S14, processing the flow field velocity data behind a single power-doing parachute to obtain processed flow field velocity data behind the power-doing parachute , as a three-dimensional sample data set.

[0014] Further: Processed flow field velocity data behind the power parachute Sample data of the recovery coefficient of the flow velocity behind the umbrella It is obtained by normalizing the wake velocity Vz behind the parachute with the mainstream velocity V as the benchmark;

[0015] Ladder inclination angle The unit is converted into radians by the parachute ladder inclination angle β;

[0016] The dimensionless spacing L / D is obtained by taking the working umbrella diameter D as the reference length and performing dimensionless processing on the working umbrella spacing L.

[0017] Further: S2 specifically includes:

[0018] S21. Select the inclination angle of the parachute ladder in the three-dimensional sample data set and the dimensionless spacing L / D combined with the dependent variable, the coefficient of recovery of the flow velocity behind the umbrella, a, as the independent variables of the symbolic regression method;

[0019] S22. Generate expressions by symbolic regression method ;

[0020] in, f is the fitting function expression of the relationship;

[0021] S23, calculate the fitting function calculation result a and the training data of the wake velocity behind the parachute The second norm error between them is used to evaluate the fitness of each candidate expression;

[0022] S24, performing inheritance, crossover and mutation operations on each candidate expression;

[0023] S25, repeating steps S23 to S24 until the number of iterations or the accuracy meets the requirements, comparing the function curves of the candidate expressions and the scatter plots of the simulation results under the same working condition, and taking the candidate expression with the smallest comparison difference as the optimal parameter expression;

[0024] S26. The optimal parameter expression is used as an evaluation model for the wake effect of the power parachute.

[0025] Further: S24 includes:

[0026] S241, using genetic algorithm to search for a and The candidate expression with the smallest two-norm error is selected, and the crossover operation is used to exchange the positions of some sample data;

[0027] S242. Use mutation operation to randomly change part of the sample data.

[0028] The beneficial effects of the present invention are:

[0029] 1. Based on the symbolic regression method, not only the relationship between the distance between the power parachutes and the degree of wake influence is analyzed, but also the influence of the inclination change of the parachute ladder during operation on the wake morphology is considered, which enriches the influencing parameter space and is more in line with the actual engineering model;

[0030] 2. It fills the gap in the reference standards for the design of working parachute spacing in the current parachute ladder system design. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a flow chart of the quantitative assessment method for the wake impact of a powered parachute facing a high-altitude parachute ladder wind catcher.

[0032] Figure 2 Schematic diagram of the spacing between working parachutes in the parachute-ladder system.

[0033] Figure 3 This is the CFD simulation flow field diagram of the working parachute at a 20° inclination angle of the parachute-ladder system.

[0034] Figure 4 This is a sampling data diagram of the flow field velocity behind the parachute at a 20° inclination angle of the parachute-ladder system.

[0035] Figure 5 is 20°< The data of flow field velocity sampling behind the working parachute under the working condition of <60°.

[0036] Figure 6 This is a comparison chart between the modeling results and the sampling data under the condition of β=60°. DETAILED DESCRIPTION

[0037] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0038] like Figure 1 As shown, in one embodiment of the present invention, a quantitative evaluation method for the wake effect of a working parachute facing a high-altitude parachute ladder wind-catching device is provided, comprising:

[0039] S1. Data preparation: According to the typical operating conditions of the parachute ladder, a three-dimensional sample data set is obtained through CFD simulation;

[0040] S2. Wake impact modeling: Based on the three-dimensional sample data set, the symbolic regression method is used to establish an evaluation model for the wake impact behind the power parachute;

[0041] S3. Quantitative evaluation: The wake impact behind a power parachute is quantitatively evaluated using an evaluation model for the wake impact behind a power parachute.

[0042] S1 includes:

[0043] S11. Based on the operating height range of the parachute ladder and the wind field conditions, determine the wind speed range and density range of the working parachute at the position of the parachute during the operation of the parachute ladder, as well as the inclination range of the parachute ladder operation;

[0044] S12, selecting wind speed V, ladder inclination angle β, and density ρ within the interval, and combining the obtained groups (V, β, ρ) as input parameters for each CFD working condition;

[0045] S13, according to the CFD input parameters of each working condition, using CFD simulation to obtain the flow field velocity data behind a single working parachute;

[0046] S14, processing the flow field velocity data behind a single power-doing parachute to obtain processed flow field velocity data behind the power-doing parachute , as a three-dimensional sample data set.

[0047] like Figure 2 As shown, the velocity data of the flow field behind the working parachute after processing Sample data of the recovery coefficient of the flow velocity behind the umbrella It is obtained by normalizing the wake velocity Vz behind the parachute with the mainstream velocity V as the benchmark;

[0048] Ladder inclination angle The unit is converted into radians by the parachute ladder inclination angle β;

[0049] The dimensionless spacing L / D is obtained by taking the working umbrella diameter D as the reference length and performing dimensionless processing on the working umbrella spacing L.

[0050] S2 specifically includes:

[0051] S21. Select the inclination angle of the parachute ladder in the three-dimensional sample data set and the dimensionless spacing L / D combined with the dependent variable, the coefficient of recovery of the flow velocity behind the umbrella, a, as the independent variables of the symbolic regression method;

[0052] S22. Generate expressions by symbolic regression method ;

[0053] in, f To express the fitting function of the relationship, the symbolic expressions required by the symbolic regression method include: addition, subtraction, multiplication, division, e-exponential, quadratic and cubic;

[0054] S23, calculate the fitting function calculation result a and the training data of the wake velocity behind the parachute The second norm error between them is used to evaluate the fitness of each candidate expression;

[0055] S24, performing inheritance, crossover and mutation operations on each candidate expression;

[0056] S24 includes:

[0057] S241, using genetic algorithm to search for a and The candidate expression with the smallest two-norm error is selected, and the crossover operation is used to exchange the positions of some sample data;

[0058] S242, using mutation operation to randomly change part of the sample data;

[0059] S25, repeating steps S23 to S24 until the number of iterations or the accuracy meets the requirements, comparing the function curves of the candidate expressions and the scatter plots of the simulation results under the same working condition, and taking the candidate expression with the smallest comparison difference as the optimal parameter expression;

[0060] S26. The optimal parameter expression is used as an evaluation model for the wake effect of the power parachute. Specific embodiment:

[0062] Collect the CFD simulation flow field data of the hemispherical parachute under the condition of variable inclination angle. Taking the 20° condition as an example, the wake shape behind the parachute is as follows: Figure 3 As shown, select Figure 3 The three lines shown in the figure define the area affected by the wake behind the parachute for sampling. Figure 4 The flow field velocity sampling data on three characteristic lines behind the hemispherical working parachute under the 20° working condition are shown;

[0063] Similarly, the above process is repeated to sample CFD simulation data under the conditions of 30°, 40°, and 50° inclination angles;

[0064] like Figure 5 The preprocessing of the flow velocity data samples behind the working parachute under the working conditions of 20°, 30°, 40° and 50° collected in S1 is shown. The one with the slowest flow velocity recovery among the three lines in S1 is taken as the characteristic line. After the tail vortex area of ​​the characteristic line, the data point where the flow velocity is greater than 0 is intercepted, the variable inclination angle β involved in the sampling data is converted into radians, and the wake velocity Vz behind the parachute is normalized with the mainstream velocity as V, and the sample data of the flow velocity recovery coefficient behind the parachute is obtained. ; Similarly, taking the diameter D of the working parachute as the reference length, the working parachute spacing L is dimensionless, and the dimensionless spacing L / D is obtained;

[0065] from Figure 6 It can be seen that the quantifiable evaluation results of the model trained by the method proposed in the present invention using only a small amount of CFD data on the impact of the 60° wake are consistent with the corresponding sampling results.

[0066] Based on a small amount of CFD data samples as shown in the above embodiments and combined with the symbolic regression modeling method, a quantitative evaluation of the wake effect behind the power parachute in the parachute ladder design process is carried out, and a new reference standard is proposed for the design of the power parachute spacing.

[0067] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A quantitative evaluation method for the wake impact of a working parachute on a high-altitude parachute ladder wind-catching device, characterized in that: include: S1. Data preparation: According to the typical operating conditions of the parachute ladder, a three-dimensional sample data set is obtained through CFD simulation; S2. Wake impact modeling: Based on the three-dimensional sample data set, the symbolic regression method is used to establish an evaluation model for the wake impact behind the power parachute; S2 includes: S21, the inclination angle of the parachute ladder in the three-dimensional sample data set The dimensionless spacing L / D is used as the independent variable of the symbolic regression method, and the recovery coefficient a of the flow velocity behind the umbrella is used as the dependent variable of the symbolic regression method; S22. Generate expressions by symbolic regression method ; in, f is the fitting function expression of the relationship; S23, the recovery coefficient a of the flow velocity behind the umbrella and the training data of the wake velocity behind the umbrella calculated according to the fitting function The second norm error between them is used to evaluate the fitness of each candidate expression; S24, performing inheritance, crossover and mutation operations on each candidate expression; S24 includes: S241, using genetic algorithm to search for a and The candidate expression with the smallest two-norm error is selected, and the crossover operation is used to exchange the positions of some sample data; S242, using mutation operation to randomly change part of the sample data; S25, repeating steps S23 to S24 until the number of iterations or the accuracy meets the requirements, comparing the function curves of the candidate expressions and the scatter plots of the simulation results under the same working condition, and taking the candidate expression with the smallest comparison difference as the optimal parameter expression; S26. Using the optimal parameter expression as an evaluation model for the wake effect of a powered parachute; S3. Quantitative evaluation: The wake impact behind a power parachute is quantitatively evaluated using an evaluation model for the wake impact behind a power parachute.

2. The quantitative evaluation method for the wake effect of a working parachute facing a high-altitude parachute ladder wind-catching device according to claim 1 is characterized in that: S1 includes: S11. Based on the operating height range of the parachute ladder and the wind field conditions, determine the wind speed range and density range of the working parachute at the position of the parachute during the operation of the parachute ladder, as well as the inclination range of the parachute ladder operation; S12, selecting wind speed V, ladder inclination angle β, and density ρ within the interval, and combining the obtained groups (V, β, ρ) as input parameters for each CFD working condition; S13, according to the CFD input parameters of each working condition, using CFD simulation to obtain the flow field velocity data behind a single working parachute; S14, processing the flow field velocity data behind a single power-doing parachute to obtain processed flow field velocity data behind the power-doing parachute , as a three-dimensional sample data set; in, is the training data of wake velocity behind the parachute, is the inclination angle of the parachute ladder, is the dimensionless spacing.

3. The quantitative evaluation method for the wake effect of a working parachute facing a high-altitude parachute ladder wind-catching device according to claim 2 is characterized in that: Processed flow field velocity data behind the power parachute Training data of wake velocity behind the parachute It is obtained by normalizing the wake velocity Vz behind the parachute with the mainstream velocity V as the benchmark; Ladder inclination angle The unit is converted into radians by the parachute ladder inclination angle β; The dimensionless spacing L / D is obtained by taking the working umbrella diameter D as the reference length and performing dimensionless processing on the working umbrella spacing L.

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