A launch vehicle safety margin design method based on probability statistics
By using a probabilistic statistical method to dynamically adjust the safety margin of rocket oxidizer and fuel, the optimal design problem of the newly developed rocket's performance and mission requirements was solved, and the overall performance of the rocket was optimized.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI AEROSPACE SYST ENG INST
- Filing Date
- 2023-06-09
- Publication Date
- 2026-06-12
AI Technical Summary
Existing technologies struggle to balance the optimal selection of rocket performance and mission requirements in the safety margin design of newly developed rockets, and conventional methods fail to consider the optimal design of overall rocket and ballistic performance.
Using a probabilistic statistical approach, a six-degree-of-freedom simulation model was established by constructing a fuel loading design model and an overall deviation model. Combined with a simulation experimental platform, the dynamic adjustment and optimal selection of the safety margin of oxidizer and fuel were carried out to optimize the rocket's exhaustion probability, landing area range, and orbital insertion probability.
The rocket achieved optimal performance design, taking into account the requirements of exhaustion probability, landing area range and orbital probability, thus improving the overall performance optimization and potential tapping of the rocket.
Smart Images
Figure CN116720257B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of aerospace technology, and in particular relates to a method for designing the safety margin of launch vehicles based on probability statistics. Background Technology
[0002] Unlike existing rocket models where the safety margins at each stage have approached optimal values through continuous flight testing and refinement, the design of safety margins for newly developed rockets faces the challenge of finding the optimal balance between rocket performance and mission requirements. In general engineering applications, safety margins are calculated based on the remaining amount corresponding to significant deviations, such as deviations in engine mixture ratio. Conventional methods are simple to calculate and can quickly obtain the remaining propellant amount under various deviations, but their design results do not consider the optimal overall rocket and ballistic performance. There is an urgent need for a safety margin design method that considers deviation probability models and statistical testing methods based on Monte Carlo simulations, capable of taking into account exhaustion probability, impact area range, and payload capacity, thereby achieving the goal of optimal rocket performance. Summary of the Invention
[0003] The technical objective of this invention is to provide a probabilistic statistical design method for the safety margin of launch vehicles, so as to achieve optimal rocket performance.
[0004] To solve the above problems, the technical solution of the present invention is as follows:
[0005] A probabilistic statistical method for designing the safety margin of launch vehicles includes the following steps:
[0006] S1: Based on the initial safety margin values of oxidizer and fuel given in conventional design, complete the refueling quantity calculation to construct the refueling quantity design model; at the same time, perform overall parameter calculation to construct the overall deviation model.
[0007] S2: A six-degree-of-freedom simulation model is established based on the fueling quantity design model and the overall deviation model. A simulation experimental platform is built in this way. The simulation experimental platform is used to statistically analyze the first-stage depletion probability, landing point deviation, and the remaining amount of second-stage oxidizer and fuel under various deviation target conditions.
[0008] S3: Determine the expected indicators, establish a feedback mechanism between statistical results and safety margin adjustment, and use the expected indicators as the optimization target to achieve dynamic adjustment and optimal selection of the safety margin of the two components of oxidant and fuel.
[0009] Specifically, in step S1, the construction of the overall deviation model involves constructing multiple refined deviation models based on the mechanism of overall deviation generation, and selecting one with a reasonable probability distribution as the overall deviation model.
[0010] Specifically, in step S2, the six-degree-of-freedom simulation model includes three elements: overall system, trajectory, and guidance.
[0011] Specifically, step S2 involves using a simulation experiment platform and ballistic optimization results as a benchmark to determine the trajectory of the guided target and the setting parameters such as the shutdown characteristics of each stage; taking the safety margin of each stage as the available quantity, and statistically analyzing the first-stage exhaustion probability, impact point deviation, and the remaining amount of second-stage oxidizer and fuel under various deviation target conditions.
[0012] Specifically, in step S3, the optimization of the safety margin of the first-stage rocket is divided into two stages. In the first stage, the landing area of the first stage is optimized and adjusted based on the initial safety margin values of oxidizer and fuel given in step S1. In the second stage, the maximum payload capacity of the first-stage rocket is optimized and adjusted based on the optimization results of the first stage.
[0013] In the first stage, the first adjustment strategy is adopted: keep the fuel depletion probability unchanged, increase the oxidant safety margin to reduce the total depletion probability, and thus reduce the landing area.
[0014] The specific steps are as follows:
[0015] Based on the initial safety margin values of oxidizer and fuel given in step S1, the safety margins of oxidizer and fuel in the first stage rocket are allocated.
[0016] The first-stage rocket was simulated using a simulation platform to obtain the probability statistics of the first-stage landing point deviation.
[0017] The probability statistics of the first-stage landing point deviation and In comparison, if Greater than Then, the first adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first stage rocket and the above steps are repeated; if Less than Then proceed to the second stage.
[0018] In the second stage, a second adjustment strategy is adopted: keeping the total depletion probability unchanged, adjusting the depletion probabilities of oxidizer and fuel, and searching for the fuel depletion probability corresponding to the maximum carrying capacity through a weighted binary search method.
[0019] The specific steps are as follows:
[0020] Based on the landing point deviation probability of the first stage's first-stage sub-class... The initial safety margin value corresponding to the above is used to allocate the safety margin of oxidizer and fuel in the first stage rocket;
[0021] The allocated first-stage rocket was simulated using a simulation platform to obtain probabilistic statistical results of its maximum payload capacity.
[0022] Probabilistic statistics on maximum carrying capacity Perform a judgment to determine whether the condition is met. and If the conditions are not met, the second adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first stage rocket and repeat the above steps; if the conditions are met, the safety margin of oxidizer and fuel in the current first stage rocket is output.
[0023] Specifically, in step S3, the safety margin of the second-stage rocket is optimized. The design goal is to have zero remaining propellant. The initial safety margin of oxidizer and fuel given in step S1 is combined with the safety margin of oxidizer and fuel optimized in the second stage as a benchmark to optimize the safety margin of oxidizer and fuel of the second-stage rocket.
[0024] Among them, the third adjustment strategy is adopted: the probability statistics of the current remaining amount of secondary propellant are converted into the safety margin adjustment value of oxidizer and fuel according to the mixing ratio, and the target is fired again;
[0025] The specific steps are as follows:
[0026] Based on the initial safety margin values of oxidizer and fuel given in step S1 and combined with the optimized safety margins of oxidizer and fuel in the second stage, the safety margins of oxidizer and fuel in the second stage rocket are allocated.
[0027] The second-stage rocket after dispensing was simulated using a simulation experimental platform to obtain the probabilistic statistical results of the remaining amount of second-stage propellant. and
[0028] Probabilistic statistics on the remaining amount of second-stage propellant and Perform a judgment to determine whether the condition is met. and If the conditions are not met, the third adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the second stage rocket and repeat the above steps; if the conditions are met, the current safety margin of oxidizer and fuel in the second stage rocket is output.
[0029] Because the present invention adopts the above technical solution, it has the following advantages and positive effects compared with the prior art:
[0030] This invention proposes a probabilistic statistical design method for the safety margin of launch vehicles. The method takes into account the requirements of exhaustion probability, landing area range and orbital probability, and carries out fine design of the safety margin of each component, creating conditions for in-depth optimization and potential tapping of the overall performance of the rocket. Attached Figure Description
[0031] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention.
[0032] Figure 1 This is a flowchart of a probabilistic statistical design method for the safety margin of a launch vehicle according to the present invention.
[0033] Figure 2 This is a flowchart of the dynamic adjustment of the first-level safety margin in this invention;
[0034] Figure 3 This is a flowchart illustrating the dynamic adjustment of the secondary safety margin in this invention. Detailed Implementation
[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without any creative effort.
[0036] To keep the drawings concise, only the parts relevant to the invention are shown schematically in each figure, and they do not represent the actual structure of the product. Furthermore, for ease of understanding, in some figures, only one of components with the same structure or function is shown schematically, or only one is labeled. In this document, "one" can mean not only "only one" but also "more than one".
[0037] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a probabilistic statistical method for designing the safety margin of launch vehicles proposed in this invention. The advantages and features of this invention will become clearer from the following description and claims.
[0038] Example
[0039] See Figures 1 to 3 This embodiment provides a probabilistic statistical method for designing the safety margin of a launch vehicle. Based on refined modeling of overall deviations, it establishes a simulated flight test platform integrating propellant loading design, trajectory, and guidance simulation. Considering the impact area of stage debris and the probability of orbital insertion, it achieves closed-loop optimization design of the safety margins for both oxidizer and fuel components. This method balances the requirements of depletion probability, impact area range, and orbital insertion probability, and conducts refined design of the safety margins for each component, creating conditions for in-depth optimization and potential tapping of the overall rocket performance. Specifically, it includes the following steps:
[0040] First, in step S1, based on existing engineering algorithms, initial safety margins for oxidizer and fuel are given, and the refueling quantity is calculated to construct a refueling quantity design model. Simultaneously, according to the mechanism of overall deviation generation, overall parameters are calculated, such as structural mass, propellant mass, center of mass position, and engine thrust. Multiple refined deviation models are constructed, and one with a reasonable probability distribution is selected as the overall deviation model, thereby reducing design margins in the process and improving overall performance.
[0041] Next, in step S2, a six-degree-of-freedom simulation model of "overall performance + trajectory + guidance" is established based on the fuel loading design model and the overall deviation model, thereby building a simulation experimental platform. Here, overall performance refers to the overall performance specialty, mainly calculating the performance parameters and deviations of the entire rocket. Performance parameters mainly include the total rocket mass, center of mass position, engine parameters, etc. Through the simulation experimental platform, using the trajectory optimization results as a benchmark, the trajectory of the guided target and the set parameters such as the shutdown characteristics of each stage are determined. The safety margins of each stage are used as available quantities, and the first-stage exhaustion probability, impact point deviation, and remaining oxidizer and fuel in the second stage are statistically analyzed under various deviation firing conditions.
[0042] Furthermore, in step S3, expected indicators are determined, such as the first-stage landing point deviation range and the remaining amount of second-stage propellant. A feedback mechanism between statistical results and safety margin adjustment is established, using the expected indicators as optimization targets to achieve dynamic adjustment and optimal selection of the safety margins of the oxidizer and fuel components.
[0043] Specifically, in step S3, the optimization of the safety margin of the first-stage rocket is divided into two stages. In the first stage, the landing area of the first stage is optimized and adjusted based on the initial safety margin values of oxidizer and fuel given in step S1. In the second stage, the maximum payload capacity of the rocket is optimized and adjusted based on the optimization results of the first stage.
[0044] The specific steps of the first stage are as follows: Based on the initial safety margin values of oxidizer and fuel given in step S1, the safety margins of oxidizer and fuel in the first-stage rocket are allocated. The allocated first-stage rocket is then simulated using a simulation platform to obtain the probabilistic statistical results of the first-stage landing point deviation. The probability statistics of the first-stage landing point deviation and In comparison, if Greater than Then, the first adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first stage rocket and the above steps are repeated; if Less than Then it proceeds to the second stage. Among them, This represents the required deviation of the first stage's impact point from the launch point, specifically the 3σ statistical value of this deviation. The first adjustment strategy involves maintaining a constant fuel depletion probability while increasing the oxidizer safety margin to reduce the overall depletion probability and thus decrease the impact zone size.
[0045] The specific steps in the second stage are as follows: Based on the first stage's first-stage landing point deviation probability... The initial safety margin values are used to allocate the safety margins of oxidizer and fuel in the first-stage rocket. The allocated first-stage rocket is then simulated using a simulation platform to obtain the probabilistic statistical results of the maximum payload capacity. Then, the probabilistic statistical results of the maximum carrying capacity. Perform a judgment to determine whether the condition is met. and If the condition is not met, the second adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first stage rocket and the above steps are repeated; if the condition is met, the current safety margin of oxidizer and fuel in the first stage rocket is output. Wherein, ε m A preset threshold is used, typically a small value, requiring the statistical values of the maximum carrying capacity to be close. The second adjustment strategy involves keeping the total depletion probability constant while adjusting the depletion probabilities of the oxidizer and fuel, using a weighted binary search method to search for the fuel depletion probability corresponding to the maximum carrying capacity.
[0046] The optimization of the safety margin for the second-stage rocket specifically aims to achieve a propellant 3σ surplus of 0. Based on the initial safety margin values for oxidizer and fuel given in step S1, combined with the optimized safety margins for oxidizer and fuel in the second stage, the safety margins for oxidizer and fuel in the second-stage rocket are allocated. The allocated second-stage rocket is then simulated using a simulation platform to obtain the probabilistic statistical results of the remaining propellant in the second stage. and Probabilistic statistics on the remaining amount of second-stage propellant and Perform a judgment to determine whether the condition is met. and If the condition is not met, the third adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the second stage rocket and the above steps are repeated; if the condition is met, the current safety margin of oxidizer and fuel in the second stage rocket is output. Wherein, ε mY This represents the expected amount of oxidant remaining, typically taken as a small value close to 0; ε mR This represents the expected value of the remaining fuel, typically a small value close to 0. The third adjustment strategy involves using the probability statistics of the current remaining secondary propellant quantity to calculate the safety margin adjustment value for oxidizer and fuel based on the mixing ratio, and then re-targeting.
[0047] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, if these changes fall within the scope of the claims of the present invention and their equivalents, they shall still fall within the protection scope of the present invention.
Claims
1. A method for designing the safety margin of a launch vehicle based on probabilistic statistics, characterized in that, Includes the following steps: S1: Based on the initial safety margin values of oxidizer and fuel given in conventional design, complete the refueling quantity calculation to construct the refueling quantity design model; at the same time, perform overall parameter calculation to construct the overall deviation model. S2: Based on the fueling design model and the overall deviation model, a six-degree-of-freedom simulation model is established to build a simulation experimental platform. Using the simulation experimental platform, the first-stage depletion probability, landing point deviation, and the remaining amount of second-stage oxidizer and fuel under various deviation target conditions are statistically analyzed. S3: Determine the expected indicators, establish a feedback mechanism between statistical results and safety margin adjustment, and use the expected indicators as the optimization target to achieve dynamic adjustment and optimal selection of the safety margin of the two components of oxidant and fuel; In step S3, the optimization of the safety margin of the first-stage rocket is divided into two stages. In the first stage, the landing area of the first-stage rocket is optimized and adjusted based on the initial safety margin values of oxidizer and fuel given in step S1. In the second stage, the maximum payload capacity of the first-stage rocket is optimized and adjusted based on the optimization results of the first stage. In the first stage, the first adjustment strategy is adopted: keep the fuel depletion probability unchanged, increase the oxidant safety margin to reduce the total depletion probability, and thus reduce the landing area. The specific steps are as follows: Based on the initial safety margin values of oxidizer and fuel given in step S1, the safety margins of oxidizer and fuel in the first-stage rocket are allocated. The simulation platform was used to simulate the first-stage rocket after allocation, and the probability statistics of the first-stage landing point deviation were obtained. ; The probability statistics of the first-stage landing point deviation and In comparison, if Greater than Then, the first adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first-stage rocket and the above steps are repeated; if Less than Then it enters the second stage; among which, This refers to the required deviation of the distance between the landing point of the first-stage rocket and the launch point. In the second stage, a second adjustment strategy is adopted: keep the total depletion probability unchanged, adjust the depletion probabilities of oxidizer and fuel, and search for the fuel depletion probability corresponding to the maximum carrying capacity through a weighted binary search method. The specific steps are as follows: Based on the first-stage sub-stage landing point deviation probability... The initial safety margin value corresponding to the above is used to allocate the safety margin of oxidizer and fuel in the first stage rocket; The simulation platform was used to simulate the allocated first-stage rocket, and the probabilistic statistical results of the maximum payload capacity were obtained. ; Probabilistic statistical results of the maximum carrying capacity Perform a judgment to determine whether the condition is met. and If the condition is not met, the second adjustment strategy is used to redistribute the safety margin of oxidizer and fuel in the first-stage rocket and the above steps are repeated; if the condition is met, the current safety margin of oxidizer and fuel in the first-stage rocket is output; wherein, This represents the probabilistic statistical result of the maximum carrying capacity calculated in the previous iteration. The preset threshold; In step S3, the safety margin of the second-stage rocket is optimized. The design goal is to have zero remaining propellant. The initial safety margin values of oxidizer and fuel given in step S1 are combined with the optimized safety margins of oxidizer and fuel in the second stage as a benchmark to optimize the safety margins of oxidizer and fuel of the second-stage rocket. The third adjustment strategy is to use the probability statistics of the current remaining amount of secondary propellant to calculate the safety margin adjustment value of oxidizer and fuel according to the mixing ratio, and then fire again. The specific steps are as follows: Based on the initial safety margin values of oxidizer and fuel given in step S1, combined with the optimized safety margins of oxidizer and fuel in the second stage, the safety margins of oxidizer and fuel in the second stage rocket are allocated. The simulation platform was used to simulate the second-stage rocket after the propellant was allocated, and the probabilistic statistics of the remaining amount of second-stage propellant were obtained. ; Probabilistic statistics on the remaining amount of second-stage propellant Perform a judgment to determine whether the condition is met. and If the conditions are not met, the safety margins of oxidizer and fuel in the second-stage rocket are redistributed using the third adjustment strategy, and the above steps are repeated; if the conditions are met, the current safety margins of oxidizer and fuel in the second-stage rocket are output; wherein, This represents the probabilistic statistical results of the remaining oxidizer in the second stage rocket. This represents the expected value of the remaining oxidant. This represents the probabilistic statistical results of the remaining fuel in the second stage rocket. This represents the expected value of the remaining fuel quantity.
2. The probabilistic statistical design method for launch vehicle safety margins according to claim 1, characterized in that, In step S1, the construction of the overall deviation model specifically involves constructing multiple refined deviation models based on the mechanism of overall deviation generation, and selecting one of the multiple refined deviation models as the overall deviation model.
3. The probabilistic statistical design method for launch vehicle safety margins according to claim 1, characterized in that, In step S2, the six-degree-of-freedom simulation model includes three elements: overall system, trajectory, and guidance.
4. The probabilistic statistical design method for launch vehicle safety margin according to claim 1, characterized in that, Specifically, step S2 involves using the simulation experimental platform and ballistic optimization results as a benchmark to determine the trajectory of the guided target and the setting parameters of each stage of shutdown characteristics; taking the safety margins of each stage as available quantities, and statistically analyzing the first-stage exhaustion probability, impact point deviation, and remaining amount of second-stage oxidizer and fuel under various deviation target conditions.