CN112149228B - Progressive matching design method for performance of solid rocket engine - Google Patents
Progressive matching design method for performance of solid rocket engine Download PDFInfo
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Abstract
The invention provides a design method for progressive matching of performance of a solid rocket engine, which comprises the following steps: acquiring a task target of a total index of the solid rocket engine; determining the number of time interval partitions according to the working time of a preset thrust requirement in a task target; obtaining an initial training sample set of the preset thrust requirement matching degree based on an initial equilibrium pressure method; operating a combustion surface and inner trajectory calculation model in an initial time interval according to an initial training sample set to obtain N thrust curves, and constructing a thrust approximation model according to the N thrust curves; performing inaccurate sampling to obtain alternative solutions; substituting the alternative solution into a combustion surface calculation model and an inner ballistic trajectory calculation model, and calculating the inner ballistic trajectory performance within simulation time to obtain an alternative thrust curve; when the simulation time is not less than the working time, adding the alternative solution serving as a new sample point into a sample set to obtain an updated sample set; and when a preset convergence condition is reached, outputting the alternative thrust curve as an optimal solution.
Description
Technical Field
The invention relates to the technical field of aerospace, in particular to a design method for progressive matching of performance of a solid rocket engine.
Background
The solid rocket engine is one of the important power systems of space vehicles such as missiles, rockets and the like. In the design problem of the solid rocket engine, a thrust-time curve is used as the most direct performance output of the engine and is also the engine performance which is most concerned by the missile. With the continuous improvement of the fine design level of the missile, the requirement on a specific thrust curve engine is more urgent. Therefore, the design of performance matching for the solid rocket engine can better meet the requirement of overall missile refinement design and improve the overall performance of missile weapons. Different from the requirement of the existing design on performance indexes, the engine performance matching design is that a group of design schemes are found in a design space, so that the obtained thrust curve is matched with the given overall index as much as possible, rather than the pure pursuit of the optimization of the engine performance, and the engine scheme obtained by adopting the mode can better meet the requirement of the missile on the engine overall. The design of matching the performance of the solid rocket engine needs to continuously call an engine performance simulation model to calculate an engine thrust curve, calculate the matching degree with the thrust requirement, drive an iterative process through an algorithm, and obtain a scheme which is as close as possible to a preset thrust curve.
When the existing method solves the problem of performance matching design, the existing commonly used method comprises the following steps: 1) the optimization problem based on the requirement and the deviation of the calculation result as the objective function is constructed, the parameter optimization is realized by combining pattern search and Particle Swarm Optimization (PSO) or Ant Colony Optimization (ACO) algorithm, and the method can only be used for matching design of two-dimensional charging because the PSO and the ACO generally need thousands of iterations. 2) And solving the matching problem by applying an optimization method based on the agent model, so that the design efficiency is improved, and the performance matching design of the three-dimensional charging configuration is realized.
However, the existing common engine matching design method has the disadvantages that: each iteration process needs to finish simulation and then fitness evaluation is carried out, repeated calculation of poor solutions is caused, calculation time consumption is increased, and low efficiency is caused.
Disclosure of Invention
The invention aims to provide a design method for progressive matching of performance of a solid rocket engine, which aims to solve the technical problems existing in the conventional engine overall design method.
In order to achieve the aim, the invention provides a design method for progressive matching of performance of a solid rocket engine, which comprises the following steps:
acquiring a task target of a total index of the solid rocket engine;
determining the number of time interval divisions and the length of the time interval according to the working time of the preset thrust requirement in the task target;
obtaining an initial training sample set X of the preset thrust requirement matching degree based on an initial equilibrium pressure methodi(i＝1,2,…,N)；
Operating a combustion surface and inner trajectory calculation model in an initial time interval according to the initial training sample set to obtain N corresponding thrust curves in the initial time interval, and constructing a thrust approximation model according to the N thrust curves;
acquiring a known thrust approximate model in simulation time, and constructing a sampling optimization objective function according to the thrust field approximate model and the N thrust curves;
sampling in the known thrust approximation model according to the sampling optimization objective function and preset sampling conditions to obtain an alternative solution;
substituting the alternative solution into a combustion surface calculation model and an inner ballistic trajectory calculation model, and calculating the inner ballistic trajectory performance within simulation time to obtain an alternative thrust curve;
when the simulation time is not less than the working time, the simulation is completed, and the alternative solution is used as a new sample point and added into a sample set to obtain an updated sample set;
and when a preset convergence condition is reached, outputting the alternative thrust curve as an optimal solution.
Further, substituting the alternative solution into a combustion surface calculation model and an inner ballistic trajectory calculation model, and calculating the inner ballistic trajectory performance within simulation time to obtain an alternative thrust curve, which comprises the following steps:
when the simulation time is shorter than the working time, carrying out simulation propulsion, simulating the combustion surface and the inner trajectory of all initial training sample points, and calculating a time interval forward to obtain the inner trajectory performance in the simulation time of the initial time interval plus the next time interval;
and when the simulation time of the current time interval plus the next time interval is less than the working time, according to the current 1+ N internal ballistic curves, eliminating the worst solution of the matching degree of the thrust requirement and the satisfying degree of the constraint, and performing cycle iteration by taking the remaining N as new initial training sample points until the simulation time is not less than the working time.
Further, when a preset convergence condition is reached, outputting the alternative thrust curve as an optimal solution, including:
the preset convergence condition is as follows: the normalized distance between the optimal d solutions in the updated sample set is less than a given precision of 0.01.
Further, an initial training sample set X of the thrust requirement matching degree is obtained based on an initial equilibrium pressure methodi(i ═ 1,2, …, N), comprising:
generating alternative samples in the task target by adopting an optimized Latin hypercube experiment;
according to the alternative sample, a CAD model of the charge is constructed, and an initial combustion surface and a charge volume are obtained;
calculating initial thrust and total thrust of the engine by utilizing a balanced pressure method and an entropy flow relation of a spray pipe according to the initial combustion surface and the charge volume to obtain design input of the alternative sample and corresponding initial thrust and total thrust;
calculating an initial thrust requirement and a total thrust requirement according to the thrust requirement, and calculating the matching degree of the initial thrust and the total thrust of the alternative sample;
according to the matching degree, selecting a sample point with the minimum matching degree from the alternative samples as an initial training sample set input Xi(i＝1,2,…,N)。
Further, according to the initial combustion surface and the charge volume, the initial thrust and the total thrust of the engine are calculated by utilizing a pressure balance method and an entropy flow relation of a spray pipe, and the design input of the alternative sample and the corresponding initial thrust and total thrust are obtained, wherein the design input of the alternative sample comprises
Design input X of the candidate sampleiAnd a corresponding initial thrust force Fi(0) General impact IiExpressed as:
wherein, XiRepresents the ithDesign variables, F, corresponding to the samplesi(0) Represents the initial thrust corresponding to the ith sample, IiRepresenting the total impulse corresponding to the ith sample;
is the total number of alternative samples.
Further, calculating an initial thrust requirement and a total thrust requirement according to the thrust requirement, and calculating the matching degree of the initial thrust and the total thrust of the candidate sample, including:
the matching degree of the initial thrust and the total impulse of the alternative sample is expressed as:
wherein, F0(0) For the initial thrust requirement of the engine, I0Is the initial total flushing requirement of the engine, Fi(0) Represents the initial thrust corresponding to the ith sample, IiDenotes the total impulse, λ, corresponding to the ith sampleiThe matching degree of the initial thrust and the total impulse corresponding to the ith sample is shown,
is the total number of alternative samples.
Further, according to the initial training sample set, operating a combustion surface and inner trajectory calculation model in an initial time interval to obtain N corresponding thrust curves in the initial time interval, including:
the N thrust curves, expressed as:
wherein, N is the total number of the initial training sample set; Δ represents a time interval length; fN(t) represents that the Nth sample is in the range of [0 to [ Delta ]]Thrust curve over time.
Further, constructing a thrust approximation model according to the N thrust curves includes:
discretizing the thrust curve to obtain k points:
wherein, TsimIndicating the time when all sample points have been simulated,
respectively constructing a thrust approximation model of each time point according to the discrete training samples;
according to the approximate model of the thrust at each time point, constructing [ 0-T ]sim]The internal thrust approximation model is represented as:
wherein,
the predicted thrust value at the jth discrete time is,
is represented by [0 to Tsim]An approximate model of thrust over time, characterized by the thrust of k discrete points.
Further, sampling in the known thrust approximation model according to the sampling optimization objective function and a preset sampling condition to obtain an alternative solution, including:
the sampling condition is expressed as:
s.t.ε≥ε0
I≥I0
L≤L0
wherein k represents a discrete number, F0(tj) Represents the j timeThrust requirement of etching, epsilon0,I0,L0And respectively representing the constraint values of the mass ratio, the total impulse and the length of the engine, and epsilon, I and L represent the design results of the mass ratio, the total impulse and the length of the engine.
The invention has the following beneficial effects:
the simulation process of the performance of the solid rocket engine takes an initial charging configuration and certain initial conditions as calculation starting points, and obtains the performance of the solid rocket engine at any time through continuous iteration on a time step until the completion of the charging process, and is characterized in that: for any time, the performance before that time is known, and the performance after that time is unknown. Therefore, the design schemes can be screened according to the matching degree obtained before the current time, if the matching degree of one scheme before the current time is poor, after the scheme is completely simulated, the matching degree is less due to the possibility of other schemes, so that the subsequent simulation of the scheme can be omitted, and the scheme can be directly judged as a poor scheme, so that the calculation amount is saved.
The invention is based on an optimization method based on a proxy model, and aims at the thrust performance matching design requirement of an engine to establish a thrust progressive matching design method so that the designed thrust curve is matched with the established thrust curve requirement as much as possible. The main idea is as follows: in the initial experiment design process, in order to avoid excessive invalid samples caused by directly adopting sample points which are uniformly distributed in space, initial sample screening based on the thrust matching degree obtained by an initial equilibrium pressure method is introduced, because in the process, only CAD modeling is needed to obtain the initial combustion surface and the charge volume (namely the initial thrust and the total charge amount), and the calculation time is far less than that of the engine performance simulation process, the sample points which are multiple times of the requirements of the initial experiment design samples can be generated, and the scheme in which the initial combustion surface and the charge amount are most consistent with the design requirements is selected as the initial samples, so that the repeated calculation of poor solutions is reduced. In the process of optimization design, when the matching performance obtained before the moment is poor, the probability of good overall performance of the sample point is low, so that the subsequent calculation of the current worst point is not necessary to be carried out continuously, and further, the calculation resources can be effectively saved. Meanwhile, because the solution of a plurality of sample points is existed before the moment, the potential optimal solution can be predicted according to the sample points, so as to obtain the sample points with better performance. At this time, since the new sample point has not been calculated yet, iterative solution needs to be performed at the point first to obtain a solution of the point before the current time and also obtain a new sample set (1 new solution and an existing result) composed of samples before the current time, all points in the sample set are iterated forward for several steps, and the worst individual can be replaced next time until all sample points are solved completely. The simulation solving time of the solid rocket engine is divided into a plurality of sections, performance evaluation (including matching performance, impact quality ratio performance, constraint satisfaction degree and the like) is carried out once when each section is calculated, and the current worst solution is removed. And simultaneously, according to the existing result, finding a better solution in the current moment and solving to the current moment, and then continuing to carry out solution iteration forward for a period of time at the same time for all points. Compared with the prior art, the method has the advantages that simulation is not completed, the optimization searching process begins to participate, poor individuals are replaced by better individuals in real time, the optimization process is mutually coupled with the solving process, and the computing resources can be remarkably saved.
The invention provides a simple, efficient and rapid design method for progressive matching of thrust of a solid rocket engine, aiming at the requirement of fine design of a thrust curve of the solid rocket engine. And when the simulation is not finished, removing the poor solution in due time according to parameters such as local thrust, pressure and the like, and reducing unnecessary calculation to save calculation resources. An approximate model based on incomplete internal trajectory parameters is constructed and used as a basis for selecting more optimal sampling points and eliminating poorer sample points, and computing resources are used for solving a more optimal solution of performance so as to improve the efficiency of optimization design.
Compared with the best technology in the prior art, the invention has the advantages that: 1. the design efficiency of the engine is improved, and invalid calculation of poor samples is avoided; 2. the invention provides a design which can better meet the requirement of special thrust by matching a design mode.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a flow chart of a solid rocket engine structure parametric design method in accordance with a preferred embodiment of the present invention;
FIG. 2 is a schematic illustration of the principal parameters of a wing-post charge of a preferred embodiment of the present invention;
FIG. 3 is a graph of single thrust engine alternative sample screening results in accordance with a preferred embodiment of the present invention;
FIG. 4 is a process diagram of a single thrust power generation progressive match design of the preferred embodiment of the present invention;
FIG. 5 is a diagram of a single thrust engine optimal solution iterative process of the preferred embodiment of the present invention;
FIG. 6 is a diagram of the preferred charge configuration for a single thrust engine according to the preferred embodiment of the present invention;
FIG. 7 is a graph of results from screening a single chamber dual thrust engine alternative sample according to a preferred embodiment of the present invention;
FIG. 8 is a graph of the progressive match design results for a single chamber dual thrust engine of the preferred embodiment of the present invention;
FIG. 9 is a diagram of an iterative process for the optimal solution of the single-chamber double-push engine in accordance with the preferred embodiment of the present invention;
fig. 10 is a diagram of an optimal charge configuration for a single chamber, twin-throw engine according to a preferred embodiment of the present invention.
Detailed Description
Embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways, which are defined and covered by the claims.
The invention provides a design method for progressive matching of performance of a solid rocket engine, which comprises the following steps:
acquiring a task target of a total index of the solid rocket engine;
determining the number of time interval divisions and the length of the time interval according to the working time of the preset thrust requirement in the task target;
obtaining an initial training sample X of the preset thrust requirement matching degree based on an initial equilibrium pressure methodi(i＝1,2,…,N)；
Operating a combustion surface and inner trajectory calculation model in an initial time interval according to the initial training sample to obtain N corresponding thrust curves in the initial time interval, and constructing a thrust approximation model according to the N thrust curves;
acquiring a known thrust approximate model in simulation time, and constructing a sampling optimization objective function according to the thrust field approximate model and the N thrust curves;
sampling in the known thrust approximation model according to the sampling optimization objective function and preset sampling conditions to obtain an alternative solution;
substituting the alternative solution into a combustion surface calculation model and an inner ballistic trajectory calculation model, and calculating the inner ballistic trajectory performance within simulation time to obtain an alternative thrust curve;
when the simulation time is not less than the working time, the simulation is completed, and the alternative solution is used as a new sample point and added into a sample set to obtain an updated sample set;
and when a preset convergence condition is reached, outputting the alternative thrust curve as an optimal solution.
In one embodiment, the general flow chart of the progressive matching design method of the solid rocket engine provided by the invention is shown in fig. 1, and the specific steps are detailed as follows.
1) Selecting basic configuration of the explosive charge according to the overall indexes, and determining design variables, objective functions and constraint conditions of an explosive charge parameterization method and an optimization model;
2) selecting reasonable design variable X according to charge parameterization method and other design parameters of engine, and determining variation range [ X ] of reasonable design variable XL,XU]；
3) Determining the number n of time interval divisions and the interval length delta as T/n according to the working time of the thrust requirement and the number d of design variables, and generally taking n as 2 d;
4) developing experimental design and sample screening, determining the number N of initial training samples according to the number d of design variables, and generally taking N as 2 d-3 d, wherein the main method comprises the following steps:
(a) based on the existing space filling test design method (such as optimized Latin hypercube experiment design, OLHD), a plurality of uniformly distributed space filling test design methods are generated in the design space
Candidate sample points (the number of the candidate sample points is generally 2-3 times of the number of the initial training samples),
(b) constructing a CAD model of the charge at the alternative sample point to obtain an initial combustion surface and a charge volume;
(c) calculating initial thrust and total thrust of the engine by utilizing a balanced pressure method and a nozzle isentropic flow relation according to an initial combustion surface and charge volume to obtain design input of a candidate sample and corresponding indexes of the initial thrust, the total thrust and the like, as shown in (1):
(d) according to thrust requirement F0(t) calculating an initial thrust demand F0(0) And initial total impact requirement I0And calculate by pressing
Initial push force and total impulse match for each sample candidate.
(e) According to the degree of matching
In that
Of the candidate samples, λ is selectediMinimum N sample points as initial training sample input Xi(i＝1,2,…,N)。
5) And for all training sample points, operating the combustion surface and inner trajectory calculation model in a first time interval to obtain N thrust curves in the first time interval, wherein the N thrust curves are represented as follows:
6) matching engine performance based on incomplete information
The time when the sample point has been simulated is recorded as TsimAccording to [0 to Tsim]Internal Engine Performance, construction [ 0-Tsim]The internal engine thrust approximates the model. Since the engine thrust is a continuous curve, not a single value, it needs to be discretized into k points:
and respectively constructing a thrust approximate model at each time point, namely a thrust field approximate model, according to the discrete training samples.
Based on [ 0-Tsim]Internal thrust approximation model
Constructing a current sampling criterion:
s.t.ε≥ε0
I≥I0
L≤L0 (6)
wherein k represents a discrete number, F0(tj) To representThrust requirement at time j, epsilon0,I0,L0And respectively representing the constraint values of the mass ratio, the total impulse and the length of the engine, and epsilon, I and L represent the design results of the mass ratio, the total impulse and the length of the engine.
Searching the formula based on the simulation time thrust approximation model by adopting an inaccurate sampling criterion to obtain an alternative solution Xnew。
7) Will alternative solution XnewSubstituting into a combustion surface calculation and inner trajectory calculation model in the range of 0 to Tsim]Calculating the inner trajectory performance to obtain [ X ]new,Fnew(t)](t∈[0,Tsim]) If T issim≥TwGo to 9); otherwise, go to 8).
8) And (5) simulating and advancing. Simulating the burning surface and the inner trajectory of all sample points, and calculating a time interval forward to obtain [ 0-T ]sim+Δ]Internal ballistic performance over time, Tsim＝Tsim+Δ。
9) And evaluating the fitness. T iswIndicating the working time.
If Tsim≥TwAdding the new sample point into the sample set, and turning to 10);
if Tsim＜TwAnd according to the current 1+ N internal ballistic curves, the worst solution is removed according to the matching degree of the thrust requirement and the satisfying degree of the constraint, the rest N internal ballistic curves are used as new sample points to complete the updating of the sample points, and the step 6) is carried out.
10) And ending judgment. If the normalized distance between the optimal d solutions in the sample set is smaller than the given precision of 0.01, stopping the calculation; otherwise go to 6).
The invention provides a simple, efficient and rapid design method for progressive matching of thrust of a solid rocket engine, aiming at the requirement of fine design of a thrust curve of the solid rocket engine. And when the simulation is not finished, removing the poor solution in due time according to parameters such as local thrust, pressure and the like, and reducing unnecessary calculation to save calculation resources. An approximate model based on incomplete internal trajectory parameters is constructed and used as a basis for selecting more optimal sampling points and eliminating poorer sample points, and computing resources are used for solving a more optimal solution of performance so as to improve the efficiency of optimization design.
The invention considers the coupling relation among the components of the engine in the overall design, changes the previous design mode, directly takes the optimization of the performance parameters of the target engine as the aim, carries out the optimization calculation on the main design parameters of each subsystem of the engine, and can effectively avoid the repeated iteration of manpower. Meanwhile, the design scheme is comprehensively optimized by the efficient optimization method based on the proxy model, and the optimization search efficiency is improved. Therefore, the method can obtain the design with the optimal comprehensive performance, and obviously improve the overall design efficiency and the comprehensive performance of the solid rocket engine.
The specific implementation of the present invention will be described with reference to the design of a single-chamber, single-thrust engine and a single-chamber, double-thrust engine.
1) Single-chamber single-thrust engine
The progressive matching design method provided by the invention is adopted to design the single-chamber single-thrust solid rocket engine, and the high efficiency of the progressive matching design method is verified. The engine design requirements are shown in table 1.
TABLE 1 Single thrust Engine design index
The standard configuration of charging is the rear wing column configuration of 8 wings, both ends are coated, and the inner hole is burnt. The definition mode is shown in fig. 2, wherein Dp is a constant value in the design process and is not used as a design variable, and the rest parameters in the figure are design variables, besides, because the expansion ratio of the nozzle has a significant influence on the engine performance and the nozzle quality, the expansion ratio and the charging geometric parameters are simultaneously used as the design variables to optimize the engine performance, and the optimization target and the constraint condition are shown in formula (4). The physical parameters of the materials required in the design process are shown in Table 2.
TABLE 2 Single thrust Engine design physical parameters
According to the number of design variables and the working time, the working time is evenly divided into 14 sections of subintervals, the simulation time of each section is 0.4 second, the number of initial experimental design sample points is 14, and the number of alternative samples is 40. Firstly, generating uniformly distributed alternative samples in a design space according to an optimized Latin hypercube experiment design method. According to the thrust requirement, the initial thrust requirement is 60kN, the total thrust requirement is 300kN · s, and the initial training sample obtained according to the alternative screening criterion is shown in fig. 3.
And starting optimization iterative design on the basis of the initial training sample. And substituting the initial sample points into the combustion surface and inner trajectory calculation model, and gradually gathering the thrust curve to the vicinity of the thrust requirement through 10 sub-optimal iterations and sample implementation replacement. With the synchronous advance of the solving and screening processes, when the solving and simulation are finished, under the driving of the algorithm, the sample sets gradually converge, and the final convergence result is shown in fig. 4.
The iterative curve of the relative mean square deviation (i.e., the mean square deviation normalized by the mean thrust) during the optimization process is shown in fig. 5. The results in the figures show that the optimal solution drops rapidly before optimization, because of the inefficient exploration performed at a large number of points in the experimental design process, and the results obtained are very different from the actual requirements. This situation results in a large amount of computational resources being used for inefficient computations if the simulation of the worse solution is not stopped in time. After the method provided by the text is adopted, one round of screening is carried out after each simulation, so that inferior solutions can be found and eliminated in time, new superior solutions are added, and the optimization capability of the solutions is improved while computing resources are saved. After 16 steps in fig. 5, the optimal solution decreases slowly, which indicates that the optimal solution is more consistent with the thrust requirement, in the process of continuing iteration, other suboptimal solutions in the sample set gradually converge towards the thrust requirement, when all samples converge to a specified error, the relative error of the solutions finally converges to 0.019, the optimal result charging configuration is shown in fig. 6, the design parameters are shown in table 3, and the results in the table indicate that the engine meets the design requirement.
TABLE 3 Single thrust Engine design results
2) Performance matching design of single-chamber double-thrust engine
Based on the progressive matching design method provided by the invention, a single-chamber double-thrust engine is designed, and the universality and the effectiveness of the method are verified. The design requirement of the engine is shown in table 4, the charging standard configuration is a rear wing column configuration with 10 wings, two ends are coated, and an inner hole is combusted. The physical parameters of the materials required in the design process are shown in table 5. The design variables and the constraint conditions are consistent with those of a single-thrust engine, the design variables are charge geometric configuration parameters and a spray pipe expansion ratio, and the constraint conditions are a total impact mass ratio.
TABLE 4 Dual thrust Engine design index
| Parameter name | Parameter value | Unit of |
| Outer diameter of engine | 800 | mm |
| First stage thrust | 360 | kN |
| First order working time | 5 | s |
| Second stage thrust | 180 | kN |
| Second stage working time | 50 | |
| Working height | ||
| 0 | km | |
| Mass ratio of | 0.86 | - |
TABLE 5 Dual thrust Engine design physical parameters
Because the combustion surface and the thrust in the charge combustion process are continuously changed, in order to facilitate the consideration of the design process on the double thrust, 10 seconds of transition time is introduced, and in the time period, the thrust is linearly changed from the primary thrust to the secondary thrust, and the design is carried out based on the continuous thrust requirement. According to the number of design variables and the working time, the working time is evenly divided into 14 sections of subintervals, the simulation time of each section is 4 seconds, the number of initial experiment design sample points is 14, and the number of alternative samples is 40. Firstly, generating uniformly distributed alternative samples in a design space according to an optimized Latin hypercube experiment design method. According to the thrust requirement, the initial thrust requirement is 360kN, the total thrust requirement is 11700kN · s, and the initial training sample obtained according to the alternative screening criterion is shown in fig. 7.
And starting optimization iterative design on the basis of the initial training sample. And substituting the initial sample points into the combustion surface and inner trajectory calculation model, and gradually gathering the thrust curve to the vicinity of the thrust requirement through 10 sub-optimal iterations and sample implementation replacement. With the synchronous advance of the solving and screening processes, when the solving and simulation are finished, under the driving of the algorithm, the sample sets gradually converge, and the final convergence result is shown in fig. 8.
By adopting the progressive matching design method provided by the invention, 14 initial samples are used for starting simulation, one-time performance estimation is carried out on the engine matching design after the simulation in each time period is completed based on the current incomplete confidence and is used for guiding the subsequent search and the simulation propulsion, and a relative mean square error iteration curve in the design process is shown in figure 9.
The results of using the algorithm herein for a single chamber dual thrust engine design are shown in table 6, which shows that the total thrust to mass ratio of the design results satisfies the design constraints. The charge configuration corresponding to the parameters in the table is shown in figure 10.
TABLE 6 Single Chamber twin Engine design results
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A design method for progressive matching of performance of a solid rocket engine is characterized by comprising the following steps:
acquiring a task target of a total index of the solid rocket engine;
determining the number of time interval divisions and the length of the time interval according to the working time of the preset thrust requirement in the task target;
obtaining an initial training sample set X of the preset thrust requirement matching degree based on an initial equilibrium pressure methodi(i＝1,2,…,N)；
Operating a combustion surface and inner trajectory calculation model in an initial time interval according to the initial training sample set to obtain N corresponding thrust curves in the initial time interval, and constructing a thrust approximation model according to the N thrust curves;
acquiring a known thrust approximate model in simulation time, and constructing a sampling optimization objective function according to the thrust field approximate model and the N thrust curves;
sampling in the known thrust approximation model according to the sampling optimization objective function and preset sampling conditions to obtain an alternative solution;
substituting the alternative solution into a combustion surface calculation model and an inner ballistic trajectory calculation model, and calculating the inner ballistic trajectory performance within simulation time to obtain an alternative thrust curve;
when the simulation time is not less than the working time, the simulation is completed, and the alternative solution is used as a new sample point and added into a sample set to obtain an updated sample set;
when a preset convergence condition is reached, outputting the alternative thrust curve as an optimal solution;
obtaining an initial training sample set X of thrust requirement matching degree based on an initial equilibrium pressure methodi(i ═ 1,2, …, N), comprising:
generating alternative samples in the task target by adopting an optimized Latin hypercube experiment;
according to the alternative sample, a CAD model of the charge is constructed, and an initial combustion surface and a charge volume are obtained;
calculating initial thrust and total thrust of the engine by utilizing a balanced pressure method and an entropy flow relation of a spray pipe according to the initial combustion surface and the charge volume to obtain design input of the alternative sample and corresponding initial thrust and total thrust;
calculating an initial thrust requirement and a total thrust requirement according to the thrust requirement, and calculating the matching degree of the initial thrust and the total thrust of the alternative sample;
according to the matching degree, selecting a sample point with the minimum matching degree from the alternative samples as an initial training sample set input Xi(i＝1,2,…,N)。
2. The design method for progressive performance matching of a solid rocket engine according to claim 1, wherein the alternative solution is substituted into a combustion surface calculation model and an inner ballistic calculation model, and the inner ballistic performance is calculated within simulation time to obtain an alternative thrust curve, comprising:
when the simulation time is shorter than the working time, carrying out simulation propulsion, simulating the combustion surface and the inner trajectory of all initial training sample points, and calculating a time interval forward to obtain the inner trajectory performance in the simulation time of the initial time interval plus the next time interval;
and when the simulation time of the current time interval plus the next time interval is less than the working time, according to the current 1+ N internal ballistic curves, eliminating the worst solution of the matching degree of the thrust requirement and the satisfying degree of the constraint, and performing cycle iteration by taking the remaining N as new initial training sample points until the simulation time is not less than the working time.
3. The design method for progressive performance matching of a solid rocket engine according to claim 1, wherein outputting the alternative thrust curve as an optimal solution when a preset convergence condition is reached comprises:
the preset convergence condition is as follows: the normalized distance between the optimal d solutions in the updated sample set is less than a given precision of 0.01.
4. The design method for progressive performance matching of a solid rocket engine according to claim 1, wherein the initial thrust and total thrust of the engine are calculated by using a pressure balance method and an entropy flow relation of a nozzle according to the initial combustion surface and charge volume, and the design input of the alternative sample and the corresponding initial thrust and total thrust are obtained, wherein the design input comprises
Design input X of the candidate sampleiAnd a corresponding initial thrust force Fi(0) General impact IiExpressed as:
wherein, XiRepresents the design variable corresponding to the ith sample, Fi(0) Represents the initial thrust corresponding to the ith sample, IiRepresenting the total impulse corresponding to the ith sample;
is the total number of alternative samples.
5. The design method for progressive matching of performance of a solid rocket engine according to claim 4, wherein calculating an initial thrust requirement and a total thrust requirement according to a thrust requirement, and calculating the matching degree of the initial thrust and the total thrust of the alternative samples comprises:
the matching degree of the initial thrust and the total impulse of the alternative sample is expressed as:
wherein, F0(0) For the initial thrust requirement of the engine, I0For the total flushing requirement of the engine, Fi(0) Represents the initial thrust corresponding to the ith sample, IiDenotes the total impulse, λ, corresponding to the ith sampleiThe matching degree of the initial thrust and the total impulse corresponding to the ith sample is shown,
is the total number of alternative samples.
6. The design method for progressive matching of performance of a solid rocket engine according to claim 1, wherein according to the initial training sample set, operating combustion surface and internal ballistic computation models in an initial time interval to obtain N thrust curves corresponding to the initial time interval comprises:
the N thrust curves, expressed as:
wherein, N is the total number of the initial training sample set; Δ represents a time interval length; fN(t) represents that the Nth sample is in the range of [0 to [ Delta ]]Thrust curve over time.
7. The progressive matching design method for performance of a solid-rocket engine according to claim 6, wherein constructing a thrust approximation model from the N thrust curves comprises:
discretizing the thrust curve to obtain k points:
wherein, TsimThe time at which the sample point simulation is completed is indicated,
respectively constructing a thrust approximation model of each time point according to the discrete training samples;
according to the approximate model of the thrust at each time point, constructing [ 0-T ]sim]The internal thrust approximation model is represented as:
wherein,
the predicted thrust value at the jth discrete time is,
is represented by [0 to Tsim]An approximate model of thrust over time, characterized by the thrust of k discrete points.
8. The design method for progressive matching of performance of a solid rocket engine according to claim 1, wherein sampling in the known thrust approximation model according to the sampling optimization objective function and preset sampling conditions to obtain alternative solutions comprises:
the sampling condition is expressed as:
s.t.ε≥ε0
I≥I0
L≤L0
wherein k represents a discrete number, F0(tj) Representing the thrust requirement at the jth instant, epsilon0,I0,L0And respectively representing the constraint values of the mass ratio, the total impulse and the length of the engine, and epsilon, I and L represent the design results of the mass ratio, the total impulse and the length of the engine.
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