Planetary Dynamic Interaction Simulation Method and System

Abstract

The present invention relates to the field of interactive simulation technology, specifically a planetary dynamic interactive simulation method and system, which includes the following steps. Based on the data input at the initial stage of simulation startup, collect the position data and velocity data of the planets, measure the planetary orbital parameters and gravitational fields by calculating the distances and relative velocities between the planets, and generate planetary interaction characteristic data. In the present invention, through real-time monitoring and dynamic data adjustment, the adaptability and accuracy of the simulation are improved. By collecting and analyzing the position and velocity data of the planets in real time, it is allowed to immediately adjust the simulation time step, so as to reflect any minor changes occurring between the planets. This adjustment ensures that during key celestial events such as planet approaches, the simulation can detail the interactions and dynamic changes between the planets. This not only reduces the waste of computing resources but also improves the accuracy of the simulation, which is particularly crucial when dealing with complex celestial interactions.

Description

Technical Field

[0001] The present invention relates to the technical field of interactive simulation, and particularly to a planetary dynamic interactive simulation method and system. Background Art

[0002] The technical field of interactive simulation mainly involves the technology of using computer systems to simulate real or fictional environments so that users can interact in real time in the environment. This technology is usually applied in the fields of training, education, research, and entertainment, and is particularly important in the simulation of the dynamic behavior of complex systems. Interactive simulation technology can provide a highly customizable and extensible environment in which physical, chemical, or biological processes can be accurately simulated, and each operation of the user will immediately affect the result of the simulation.

[0003] Among them, the planetary dynamic interactive simulation method is a specific interactive simulation application dedicated to simulating and analyzing the process of planetary motion and its dynamic interaction. This method can effectively simulate the gravitational interaction between planets, orbital changes, and the interaction between planets and other celestial bodies (such as satellites, asteroids) in astronomical research and space mission planning. In addition, this method is also widely used in the education field, helping students understand and explore the complex dynamics of the universe by providing an intuitive simulation interface.

[0004] When traditional methods simulate complex celestial dynamics, they cannot update data in a timely manner and it is difficult to accurately capture and reflect sudden events between planets, such as the situation where an asteroid approaches a large planet quickly. This sluggish response results in the simulation results not being able to reflect the real interaction between celestial bodies in real time, affecting the authenticity and scientific nature of the simulation and limiting the application effect in high-precision scientific research tasks and education. In addition, the lack of a mechanism to flexibly adjust the simulation accuracy limits its application in fields that require highly accurate control, such as deep space exploration mission planning and complex celestial body behavior prediction. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art and to propose a planetary dynamic interactive simulation method and system.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: A planetary dynamic interactive simulation method, including the following steps,

[0007] S1: Based on the data input at the initial stage of simulation startup, collect the position data and velocity data of the planets, measure the planetary orbital parameters and gravitational fields by calculating the distances and relative velocities between the planets, and generate planetary interaction characteristic data;

[0008] S2: Based on the planetary interaction characteristic data, evaluate the computational load in the planetary interaction mechanics model, adjust the time step of the simulation, and optimize the processing speed to obtain time step optimization data;

[0009] S3: Optimize the data based on the time step, monitor and record the occurrence of planet approach events and key celestial body events in real time. Meanwhile, detect the newly generated planet position and velocity data during the simulation process, and finely adjust the time step to obtain refined step data;

[0010] S4: Based on the refined step data, at the end of the simulation cycle, adopt the incremental data integration technology to merge the new data generated in the simulation with the existing data, and analyze the events during the simulation cycle to generate comprehensive simulation cycle data.

[0011] The improvement of the present invention is that the calculation steps of the distance and relative velocity between the planets are specifically as follows:

[0012] S111: According to the data input at the initial stage of the simulation, extract the position coordinates and velocity vectors of each planet to obtain a planet position and velocity information table;

[0013] S112: Based on the planet position and velocity information table, use the formulas:

[0014]

[0015] and

[0016]

[0017] Calculate the Euclidean distance d between the planets ij and the relative velocity v rel，ij , where a1, a2, and a3 are weight coefficients for adjusting the accuracy of planet position data, used to affect the accuracy of calculating the distance between planets, and b1, b2, and b3 are weight coefficients for adjusting the accuracy of planet velocity data, used to affect the accuracy of relative velocity calculation, x i , y i and z i and x j , y j and z j are the three-dimensional position coordinates of two planets, used to represent the absolute positions of the planets in the simulation space, v x，i , v y，i and v z，i and v x，j , v y，j and v z，j are the corresponding velocity vector components, used to calculate the relative motion velocity between planets.

[0018] The improvement of the present invention is that the measurement steps of the planet orbital parameters and gravitational field are specifically as follows:

[0019] S121: Using the obtained distance and relative velocity between the planets, use the formula:

[0020]

[0021] Calculate the gravitational force F ij , where c is the speed of light, v rel，ij is the relative velocity between planets, d ij is the distance between planets, m i and m j are the masses of two planets, α is a parameter that adjusts the gravitational calculation and combines the influence of motion, and G is the gravitational constant;

[0022] S122: Based on the planetary position data and the gravitational force F ij , use the formula:

[0023]

[0024] Calculate the orbital radius r orb and eccentricity e of the planet, where E is the total energy, L is the total angular momentum, m i and m j are the masses of two planets, and G is the gravitational constant;

[0025] S123: Combine the gravitational forces between planets with the planetary orbital parameters, analyze the stability and dynamic characteristics of the planetary system, and obtain the planetary interaction characteristic data.

[0026] The improvement of the present invention is that the step of obtaining the time step optimization data is specifically as follows:

[0027] S211: Based on the planetary interaction characteristic data, calculate the computational load for each time step of the simulation, using the formula:

[0028]

[0029] where d ij is the distance between planets, v rel，ij is the relative velocity, v th is the velocity threshold, α and β are adjustment coefficients, and ∈ is a small adjustment coefficient for distance, used to adjust the influence of distance on the load, to obtain the computational load L for each time step;

[0030] S212: According to the computational load L and the set performance standard P, adjust the time step Δt, using the formula:

[0031]

[0032] where γ is a small constant added to avoid a zero denominator, to obtain the adjusted time step Δt;

[0033] S213: Compare the adjusted time step Δt with the original time step, analyze the optimization effect, and obtain the time step optimization data.

[0034] The improvement of the present invention is that the detection step of the newly generated planetary position and velocity data is specifically as follows:

[0035] S311: Based on the time step optimization data, collect the position and velocity data of the planet in real time to obtain the current motion state of the planet;

[0036] S312: Analyze the continuously collected planetary position and velocity data, calculate the position change Δpos and velocity change Δvel within each simulation time step, and use the formula:

[0037] Δpos = pos current - pos previous

[0038] and

[0039] Δvel = vel current - vel previous

[0040] where pos current and vel current represent the position and velocity at the current time step respectively, and pos previous and vel previous represent the position and velocity at the previous time step;

[0041] S313: Use the rate of change formula to calculate the change trends of the planetary position and velocity, and evaluate the stability and dynamic behavior of the simulation:

[0042]

[0043] Obtain the newly generated planetary position and velocity data, where α and β are weighting factors used to control the influence of position and velocity changes, κ is an adjustment coefficient used to adjust the overall sensitivity of the trend, Δt is the current time step, r is the power of the time step used to adjust the influence of time, and p and q are powers used to optimize the non - linear influence of position and velocity changes.

[0044] The improvement of the present invention is that the obtaining step of the refined adjusted step - size data is specifically as follows:

[0045] S321: According to the newly generated planetary position and velocity data, analyze with the current time step, and adjust the time step using the formula to respond to the changes in the planet dynamics:

[0046]

[0047] Obtain the new time step Δtnew , where λ is the sensitivity adjustment parameter that controls the sensitivity of trend changes to time step adjustment, σ is the exponent of the trend influence intensity to optimize the non-linear influence, ν is the root number of the time adjustment intensity for refining the influence of time step adjustment, and Δt is the current time step;

[0048] S322: Evaluate the newly calculated time step Δt new and compare it with the current time step Δt to obtain the step data for refined adjustment.

[0049] The improvement of the present invention is that the specific steps for merging the new data and the existing data are as follows:

[0050] S411: Based on the step data for refined adjustment, collect the new data generated at the end of the simulation cycle and extract the data that already existed before the start of the simulation cycle;

[0051] S412: Use the formula to integrate the new data and the existing data:

[0052]

[0053] where λ is the merging coefficient of the new data, which is used to determine the weight of the new data in the integration, α and β are adjustment parameters for optimizing the non-linear influence when merging the new data and the existing data, D new and D existing are the newly generated data and the existing data respectively, and D combined is the merged data set.

[0054] The improvement of the present invention is that the specific steps for obtaining the comprehensive data of the simulation cycle are as follows:

[0055] S421: Analyze the generated new data and the existing data to identify the key events and trends within the simulation cycle;

[0056] S422: Use data analysis techniques to classify and evaluate the identified events, using the formula:

[0057]

[0058] where θ is the analysis sensitivity parameter for adjusting the degree of the data analysis process, γ is the weighting factor for optimizing the influence of the original data on the analysis result, k is the non-linear response index for optimizing the sensitivity of data features, κ is the normalization factor, A results is the analysis result, and D combined is the merged data set;

[0059] S423: According to the analysis result A results and the merged data set D combined , use the formula:

[0060]

[0061] Obtain the comprehensive data S of the simulation cycle cycle , where ξ and η are weighting parameters used to adjust the influence on the data, and ρ is a normalization coefficient used to balance the proportion of the data.

[0062] Planetary dynamic interaction simulation system, the system includes:

[0063] The planetary data acquisition module collects the position data and velocity data of the planets based on the data input at the initial stage of the simulation start, calculates the distances and relative velocities between the planets, and measures the planetary orbit parameters and gravitational fields to obtain the planetary interaction characteristic data;

[0064] The load evaluation and optimization module evaluates the computational load of the planetary interaction mechanical model based on the planetary interaction characteristic data, adjusts the time step of the simulation according to the calculation results, reallocates the computing resources according to the adjusted time step, optimizes the processing speed, and obtains the optimized time step data;

[0065] The real-time monitoring and adjustment module uses the optimized time step data to monitor the planetary approach events and key celestial body events, adjusts the time step according to the event occurrence frequency, refines the time granularity of the simulation, and obtains the refined adjustment step data;

[0066] The data integration and analysis module applies the incremental data integration technology based on the refined adjustment step data, merges the newly generated data and the existing data in the simulation, analyzes the events within the simulation cycle, extracts key information, and obtains the comprehensive data of the simulation cycle;

[0067] The system output and log module integrates the key celestial body events and the data of planetary dynamic interaction according to the comprehensive data of the simulation cycle, formulates the simulation log and charts, and forms the planetary dynamic analysis record.

[0068] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0069] In the present invention, through real-time monitoring and dynamic data adjustment, the adaptability and accuracy of the simulation are improved. The position and velocity data of the planets are collected and analyzed in real time, allowing for immediate adjustment of the simulation time step to reflect any minor changes that occur between the planets. This adjustment ensures that during key celestial body events such as planetary approach, the simulation can accurately reflect the interactions and dynamic changes between the planets, not only reducing the waste of computing resources but also improving the accuracy of the simulation, which is particularly crucial when dealing with complex celestial interactions. By merging new and old data, the refined adjustment step data further enhances the coherence and reliability of the simulation results, providing more accurate data support. Brief Description of the Drawings

[0070] Figure 1 This is a flowchart of the planetary dynamic interaction simulation method proposed by the present invention;

[0071] Figure 2 This is a schematic diagram of the calculation process of the distance and relative velocity between planets in the planetary dynamic interaction simulation method proposed by the present invention;

[0072] Figure 3 This is a schematic diagram of the measurement process of the planetary orbit parameters and gravitational field in the planetary dynamic interaction simulation method proposed by the present invention;

[0073] Figure 4 This is a schematic diagram of the acquisition process of the optimized time step data in the planetary dynamic interaction simulation method proposed by the present invention;

[0074] Figure 5 This is a schematic diagram of the detection process of the newly generated planetary position and velocity data in the planetary dynamic interaction simulation method proposed by the present invention;

[0075] Figure 6 This is a schematic diagram of the acquisition process of the refined adjustment step data in the planetary dynamic interaction simulation method proposed by the present invention;

[0076] Figure 7 This is a schematic diagram of the merging process of the new data and the existing data in the planetary dynamic interaction simulation method proposed by the present invention;

[0077] Figure 8 This is a schematic diagram of the acquisition process of the comprehensive simulation cycle data in the planetary dynamic interaction simulation method proposed by the present invention. Detailed Embodiment

[0078] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0079] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, in the description of the present invention, the meaning of "plurality" is two or more unless otherwise specifically defined.

[0080] Embodiment

[0081] Please refer to Figure 1 , the present invention provides a technical solution: a planetary dynamic interaction simulation method, including the following steps:

[0082] S1: Based on the data input at the initial stage of simulation startup, collect the position data and velocity data of the planets, measure the planetary orbit parameters and gravitational fields by calculating the distances and relative velocities between the planets, and generate planetary interaction characteristic data;

[0083] S2: Based on the planetary interaction characteristic data, evaluate the computational load in the planetary interaction mechanics model, adjust the time step of the simulation, and optimize the processing speed to obtain time step optimization data;

[0084] S3: Based on the time step optimization data, monitor and record in real time the occurrence of planetary approach events and key celestial body events, and at the same time detect the newly generated planetary position and velocity data during the simulation process, and fine-tune the time step to obtain refined adjustment step data;

[0085] S4: Based on the refined adjustment step data, at the end of the simulation cycle, adopt incremental data integration technology to merge the new data generated in the simulation with the existing data, and analyze the events during the simulation cycle to generate simulation cycle comprehensive data.

[0086] The planetary interaction characteristic data includes planetary trajectory data, velocity vectors, and mutual force indices. The time step optimization data includes time adjustment factors, computational efficiency ratios, and resource consumption rates. The refined adjustment step data includes adjustment accuracy information, step variation indices, and response speed information. The simulation cycle comprehensive data includes event frequency distribution data, simulation stability evaluation results, and data continuity evaluation results.

[0087] Please refer to Figure 2 , the calculation steps of the distances and relative velocities between the planets are specifically as follows:

[0088] S111: According to the data input at the initial stage of simulation startup, extract the position coordinates and velocity vectors of each planet to obtain a planetary position and velocity information table;

[0089] S112: Based on the planetary position and velocity information table, use the formulas:

[0090]

[0091] and

[0092]

[0093] to calculate the Euclidean distance d ij and the relative velocity v rel，ij, where a1, a2, and a3 are the weight coefficients for adjusting the accuracy of planetary position data, used to affect the accuracy of calculating the distance between planets, and b1, b2, and b3 are the weight coefficients for adjusting the accuracy of planetary velocity data, used to affect the accuracy of relative velocity calculation, x i , y i and z i and x j , y j and z j are the three-dimensional position coordinates of two planets, used to represent the absolute positions of the planets in the simulation space, v x，i , v y，i and v z，i and v x，j , v y，j and v z，j are the corresponding velocity vector components, used to calculate the relative motion velocity between planets.

[0094] Suppose there are two planets A and B, and their position coordinates and velocity vectors are as follows:

[0095] Position coordinates of planet A: (x A , y A , z A ) = (1, 2, 3);

[0096] Position coordinates of planet B: (x B , y B , z B ) = (4, 6, 8);

[0097] Velocity vector of planet A: (v x，A , v y，A , v z，A ) = (2, 3, 1);

[0098] Velocity vector of planet B: (v x，B , v y，B , v z，B ) = (1, 0, 5).

[0099] Calculate the distance d between the planets AB

[0100] Calculate the difference in position coordinates between planets A and B:

[0101] Δx = x B - X A = 4 - 1 = 3

[0102] Δy = y B - y A = 6 - 2 = 4

[0103] Δz = z B - zA = 8 - 3 = 5

[0104] Calculate the distance between two planets using the Euclidean distance formula, assuming that the weight coefficients a1, a2, and a3 are all set to 1 (no additional weighting):

[0105]

[0106] Calculate the relative velocity v between the planets rel，AB

[0107] Calculate the difference in velocity vectors between planets A and B:

[0108] Δv x = v x，B - v x，A = 1 - 2 = -1

[0109] Δv y = v y，B - v y，A = 0 - 3 = -3

[0110] Δv z = v z，B - v z，A = 5 - 1 = 4

[0111] Calculate the relative velocity between two planets using the Euclidean formula for relative velocity, assuming that the weight coefficients b1, b2, and b3 are all set to 1 (no additional weighting):

[0112]

[0113] Obtain the distance and relative velocity between the planets from the position and velocity data input by the simulation.

[0114] Please refer to Figure 3 , the measurement steps for the planetary orbital parameters and gravitational field are specifically as follows:

[0115] S121: Using the obtained distance and relative velocity between the planets, use the formula:

[0116]

[0117] Calculate the gravitational force F ij , where c is the speed of light, v rel，ij is the relative velocity between the planets, d ij is the distance between the planets, m i and m j are the masses of the two planets, α is a parameter that adjusts the gravitational calculation and incorporates the influence of motion, and G is the gravitational constant;

[0118] S122: Based on the planetary position data and the gravitational force Fij , use the formula:

[0119]

[0120] to calculate the orbital radius r of the planet orb and the eccentricity e, where E is the total energy, L is the total angular momentum, m i and m j are the masses of two planets, and G is the gravitational constant;

[0121] S123: Combine the gravitational forces between planets with the planetary orbital parameters to analyze the stability and dynamic characteristics of the planetary system and obtain the planetary interaction characteristic data.

[0122] Calculate the gravitational force F ij :

[0123] Assume the masses of the two planets are:

[0124] m i = 5.97×10 24 lg (mass similar to Earth) and m j = 7.35×10 22 kg (mass similar to the Moon);

[0125] The distance d between the two planets ij = 384,400 km (distance between the Earth and the Moon);

[0126] The gravitational constant G = 6.674×10 -11 m 3 kg -1 s -2 ;

[0127] The relative velocity v rel，ij = 1,022 m / s;

[0128] The speed of light c = 3×10 8 m / s;

[0129] Adjust the parameter α = 0.001.

[0130] Substitute the specific values using the formula:

[0131]

[0132] F ij = 1.982×10 20 (1 + 1.115×10 -8 )

[0133] F ij ≈1.982×10 20 N

[0134] Calculate the orbital parameters of the planet:

[0135] Use the calculated gravitational force F ij , assuming the total energy of the planetary system is E = -1.2×10 29 J, and the total angular momentum L = 2.9×10 34 Js.

[0136] Calculate the orbital radius r orb and the eccentricity e:

[0137]

[0138] Based on the calculated orbital parameters and gravitational force, analyze the stability and dynamic characteristics of the planetary system, and output a comprehensive report.

[0139] Please refer to Figure 4 , the specific steps for obtaining the optimized data of the time step are as follows:

[0140] S211: Based on the planetary interaction characteristic data, calculate the computational load for each time step of the simulation, using the formula:

[0141]

[0142] where d ij is the distance between planets, v rel，ij is the relative velocity, v th is the velocity threshold, α and β are adjustment coefficients, and ∈ is a small adjustment coefficient for distance, used to adjust the influence of distance on the load, to obtain the computational load L for each time step;

[0143] S212: According to the computational load L and the set performance standard P, adjust the time step Δt, using the formula:

[0144]

[0145] where γ is a small constant added to avoid a zero denominator, to obtain the adjusted time step Δt;

[0146] S213: Compare the adjusted time step Δt with the original time step, analyze the optimization effect, and obtain the optimized data of the time step.

[0147] Assume parameters:

[0148] The distance d between planets ij = 10∧8m;

[0149] The relative velocity v rel，ij = 1000m / s;

[0150] The velocity threshold vth = 500 m / s;

[0151] The adjustment coefficient α = 0.5;

[0152] The velocity exponent β = 2;

[0153] The distance adjustment coefficient ∈ = 0.1;

[0154] The performance standard P = 0.01 s;

[0155] The small constant γ = 0.001.

[0156] Substitute specific values to calculate the computational load L:

[0157]

[0158] Substitute specific values to adjust the time step Δt of the simulation:

[0159]

[0160]

[0161] Δt ≈ 0.31623 s

[0162] The computational load L: It is calculated using the output parameters of the simulation model. The adjusted parameters α, β, and ∈ are used to precisely control the sensitivity of the computational load to distance and speed according to the distance and relative speed between planets;

[0163] The time step Δt: Adjust the time step according to the calculated load L to ensure a balance between simulation efficiency and accuracy. The small constant γ ensures that the time step will not be too large at extremely low loads.

[0164] Please refer to Figure 5 , and the specific detection steps for the newly generated planetary position and velocity data are as follows:

[0165] S311: Optimize the data based on the time step, collect the position and velocity data of the planets in real time, and obtain the current motion state of the planets;

[0166] S312: Analyze the continuously collected planetary position and velocity data, calculate the position change Δpos and velocity change Δvel within each simulation time step, using the formulas:

[0167] Δpos = pos current - pos previous

[0168] and

[0169] Δvel = vel current - vel previous

[0170] Among them, pos current and vel current respectively represent the position and velocity at the current time step, pos previous and vel previous represent the position and velocity at the previous time step;

[0171] S313: Use the rate of change formula to calculate the trends of the planetary position and velocity, and evaluate the stability and dynamic behavior of the simulation:

[0172]

[0173] Obtain the newly generated planetary position and velocity data. Among them, α and β are weighting factors used to control the impact of position and velocity changes, κ is an adjustment coefficient used to adjust the overall sensitivity of the trend, Δt is the current time step, r is the power of the time step used to adjust the impact of time, and p and q are powers used to optimize the non-linear impact of position and velocity changes.

[0174] Assumed parameters and data:

[0175] Assume that at a certain simulation time point, the position of planet A, pos current =(300, 300, 300) km;

[0176] The position at the previous time step, pos previous =(290, 290, 290) km;

[0177] The current velocity, vel current =(2, 2, 2) km / s;

[0178] The velocity at the previous time step, vel previous =(1.5, 1.5, 1.5) km / s;

[0179] The time step, Δt = 10 s;

[0180] The weighting factors, α = 0.6, β = 0.4;

[0181] The powers, p = 1.5, q = 1.2;

[0182] The time power, r = 0.8;

[0183] The adjustment coefficient, κ = 0.75.

[0184] Substitute the values and calculate the position change (Δpos):

[0185] Δpos = pos current - pos previous=(300 - 290, 300 - 290, 300 - 290) = (10, 10, 10) km

[0186] Calculate the velocity change (Δvel):

[0187] Δvel = vel current - vel previous =(2 - 1.5, 2 - 1.5, 2 - 1.5) = (0.5, 0.5, 0.5) km / s

[0188] Substitute the values and calculate the trend:

[0189]

[0190] trend ≈ 2.28

[0191] Please refer to Figure 6 , and the specific steps for obtaining the refined adjustment step - size data are as follows:

[0192] S321: Analyze the newly generated planet position and velocity data with the current time step, and adjust the time step using the formula to respond to the changes in the planet's dynamics:

[0193]

[0194] Obtain the new time step Δt new , where λ is the adjustment sensitivity parameter that controls the sensitivity of the trend change to the time - step adjustment, σ is the exponent of the trend influence intensity to optimize the non - linear influence, ν is the root number of the time adjustment intensity used to refine the influence of the time - step adjustment, and Δt is the current time step;

[0195] S322: Evaluate the newly calculated time step Δt new and compare it with the current time step Δt to obtain the refined adjustment step - size data.

[0196] Suppose there are the following data:

[0197] Current time step (Δt): 0.1 second;

[0198] Dynamic trend (trend): 0.5;

[0199] Adjustment sensitivity parameter (λ): 0.05;

[0200] Exponent of the trend influence intensity (σ): 2;

[0201] Root number of the time adjustment intensity (ν): 3.

[0202] Substitute the specific values:

[0203]

[0204] Δt new = 0.1·0.99862

[0205] Δt new = 0.099862 seconds

[0206] The newly calculated time step Δt new is 0.099862 seconds, which is slightly reduced compared to the original time step, showing fine-tuning according to the planetary dynamic trend. Comparing the new time step with the original time step, record the specific values and ratios of the fine-tuning to provide data support for the accuracy and performance optimization of subsequent simulation cycles.

[0207] Please refer to Figure 7 , the specific steps for merging new data with existing data are as follows:

[0208] S411: Based on the step data refined and adjusted, collect the new data generated at the end of the simulation cycle and extract the data that already existed before the start of the simulation cycle;

[0209] S412: Use the formula to integrate the new data and the existing data:

[0210]

[0211] where λ is the merging coefficient of the new data, used to determine the weight of the new data in the integration, and α and β are adjustment parameters, used to optimize the non-linear influence when merging the new data and the existing data, D new and D existing are the newly generated data and the existing data respectively, and D combined is the merged data set.

[0212] Suppose there is the following data:

[0213] New data (D new ): 50 (representing the value of the newly added data);

[0214] Existing data (D existing ): 100 (representing the value of the existing data);

[0215] Merging coefficient (λ): 0.3 (determining the weight of the new data in the merging);

[0216] Adjustment parameters (α and β): 2, 1 (enhancing the non-linear influence of the new data).

[0217] Substitute the specific values for calculation:

[0218]

[0219] Dcombined ≈273.33

[0220] D new New data, used to reflect the latest simulation results, D existing Existing data, including the results accumulated in previous simulation cycles, the λ merging coefficient, which affects the relative importance of new data during the integration process, and the α and β non - linear adjustment parameters, which are used to enhance the influence of new and old data during the data merging process. In this example, a higher α means that new data is given a stronger non - linear weighting, while a lower β indicates that existing data is weighted linearly.

[0221] Through this calculation process, it can be seen that the merged data D combined is approximately 273.33. This value combines the influence of new data and existing data and increases the influence of new data through non - linear adjustment parameters. This method ensures the flexibility and adaptability of data merging, enabling the merged data to better reflect the latest developments and historical accumulations of the simulation.

[0222] Please refer to Figure 8 , the specific steps for obtaining the comprehensive data of the simulation cycle are as follows:

[0223] S421: Analyze the generated new data and existing data to identify key events and trends within the simulation cycle;

[0224] S422: Use data analysis techniques to classify and evaluate the identified events, using the formula:

[0225]

[0226] where θ is the analysis sensitivity parameter, used to adjust the degree of the data analysis process, γ is the weighting factor, used to optimize the influence of the original data on the analysis results, k is the non - linear response index, optimizing the sensitivity of data characteristics, κ is the normalization factor, A results is the analysis result, D combined is the merged data set;

[0227] S423: According to the analysis result A results and the merged data set D combined , use the formula:

[0228]

[0229] to obtain the comprehensive data S of the simulation cycle cycle , where ξ and η are weighting parameters, used to adjust the influence on the data, and ρ is the normalization coefficient, used to balance the proportion of the data.

[0230] Suppose there is the following data:

[0231] Combined dataset (D combined ): Assume it is 120 (number of data points);

[0232] Analysis sensitivity parameter (θ): Assume it is 0.8 (used to adjust the sensitivity of the analysis);

[0233] Weighting factor (γ): Assume it is 1.5 (enhance the influence of data features);

[0234] Nonlinear response index (k): Assume it is 2 (used to increase the nonlinear influence of data);

[0235] Normalization factor (k): Assume it is 3 (used to stabilize the analysis results);

[0236] Weighting parameter (ξ): Assume it is 2 (adjust the influence of the analysis results);

[0237] Weighting parameter (η): Assume it is 1 (adjust the influence of the combined dataset);

[0238] Normalization coefficient (ρ): Assume it is 5 (used to balance the proportion of comprehensive data).

[0239] Apply data analysis techniques and substitute specific values for calculation:

[0240]

[0241] Assume the analyze function simply multiplies D combined by θ:

[0242]

[0243] Substitute values for calculation to obtain comprehensive data for the simulation period:

[0244]

[0245] Ensure the accuracy and applicability of the final output through processing and analyzing the simulation data.

[0246] Planetary dynamic interaction simulation system, the system includes:

[0247] The planetary data acquisition module collects the position data and velocity data of the planets based on the data input at the initial stage of the simulation, calculates the distances and relative velocities between the planets, and measures the planetary orbit parameters and gravitational fields to obtain planetary interaction characteristic data;

[0248] The load evaluation and optimization module evaluates the computational load of the planetary interaction mechanical model based on the planetary interaction characteristic data, adjusts the time step of the simulation according to the calculation results, reallocates computing resources based on the adjusted time step, optimizes the processing speed, and obtains time step optimization data;

[0249] The real-time monitoring and adjustment module optimizes data using the time step, monitors planet approach events and key celestial body events, adjusts the time step according to the event occurrence frequency, refines the time granularity of the simulation, and obtains the step data with refined adjustment;

[0250] The data integration and analysis module, based on the step data with refined adjustment, applies incremental data integration technology to merge the newly generated data and the existing data in the simulation, analyzes the events within the simulation cycle, extracts key information, and obtains the comprehensive data of the simulation cycle;

[0251] The system output and log module, according to the comprehensive data of the simulation cycle, integrates the data of key celestial body events and planet dynamic interactions, formulates simulation logs and charts, and forms a record of planet dynamic analysis.

[0252] The above are only the preferred embodiments of the present invention, and do not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. Planetary dynamic interaction simulation method, characterized in that, Including the following steps: Based on the data input at the initial stage of simulation startup, collect the position data and velocity data of the planets, measure the planetary orbital parameters and gravitational fields by calculating the distances and relative velocities between the planets, and generate planetary interaction characteristic data; Based on the planetary interaction characteristic data, evaluate the computational load in the planetary interaction mechanics model, adjust the time step of the simulation, and optimize the processing speed to obtain time step optimization data; The specific steps for obtaining the time step optimization data are as follows: Based on the planetary interaction characteristic data, calculate the computational load for each time step of the simulation, using the formula: ； Among them, is the distance between planets, is the relative velocity, is the velocity threshold, and are adjustment coefficients, is a small adjustment coefficient for distance, used to adjust the influence of distance on the load to obtain the calculated load L at each time step; Adjust the time step according to the calculated load L and the set performance standard P , using the formula: ； Among them, is a small constant added to avoid a zero denominator, and the adjusted time step is obtained; The adjusted time step is compared with the original time step to analyze the optimization effect and obtain the time step optimization data; Based on the time step optimization data, monitor and record in real time the occurrence of planet approach events and key celestial body events, and at the same time detect the newly generated planetary position and velocity data during the simulation process, and make fine adjustments to the time step to obtain refined adjustment step data; Based on the refined adjustment step data, at the end of the simulation cycle, use incremental data integration technology to merge the newly generated data and the existing data in the simulation, and analyze the events during the simulation cycle to generate simulation cycle comprehensive data.

2. The planetary dynamic interaction simulation method according to claim 1, wherein The specific steps for calculating the distances and relative velocities between the planets are as follows: According to the data input at the initial stage of simulation startup, extract the position coordinates and velocity vectors of each planet to obtain a planetary position and velocity information table; Based on the planetary position and velocity information table, use the formula: ， and ； Calculate the Euclidean distance between planets and the relative velocity , where , and are the weight coefficients for adjusting the accuracy of the planetary position data, which are used to affect the accuracy of calculating the distance between planets, , and are the weight coefficients for adjusting the accuracy of the planetary velocity data, which are used to affect the accuracy of calculating the relative velocity, , and and , and are the three-dimensional position coordinates of two planets, which are used to represent the absolute positions of the planets in the simulation space, , and and , and are the corresponding velocity vector components, which are used to calculate the relative motion velocity between planets.

3. The planetary dynamic interaction simulation method according to claim 2, wherein The specific steps for measuring the planetary orbital parameters and gravitational fields are as follows: Using the obtained distances and relative velocities between the planets, use the formula: ， Calculate the gravitational force , where c is the speed of light, is the relative velocity between planets, is the distance between planets, and are the masses of two planets, is a parameter that adjusts the gravitational calculation and incorporates the influence of motion, and G is the gravitational constant; Based on planetary position data and gravitational forces , use the formula: ， Calculate the orbital radius of the planet and the eccentricity e, where E is the total energy, L is the total angular momentum, and are the masses of the two planets, and G is the gravitational constant; Combining the gravitational forces between the planets and the planetary orbital parameters, analyze the stability and dynamic characteristics of the planetary system to obtain planetary interaction characteristic data.

4. The planetary dynamic interaction simulation method according to claim 1, wherein The specific steps for detecting the newly generated planetary position and velocity data are as follows: Based on the time step optimization data, collect in real time the position and velocity data of the planets to obtain the current motion state of the planets; Analyze the continuously collected planetary position and velocity data to calculate the position change within each simulation time step and the velocity change , using the formula: ， and ； Among them, and respectively represent the position and velocity at the current time step, and represent the position and velocity at the previous time step; Using the rate of change formula, calculate the change trends of the planetary positions and velocities, and evaluate the stability and dynamic behavior of the simulation: ， Obtain the newly generated planetary position and velocity data, where, and are weighting factors used to control the influence of position and velocity changes, is an adjustment coefficient used to adjust the overall sensitivity of the trend, is the current time step, r is the power of the time step used to adjust the influence of time, and p and q are powers used to optimize the non-linear influence of position and velocity changes.

5. The planetary dynamic interaction simulation method according to claim 4, characterized in that, The specific steps for obtaining the refined adjustment step data are as follows: According to the newly generated planetary position and velocity data, analyze with the current time step, and adjust the time step using the formula to respond to the changes in the planetary dynamics: ， Obtain a new time step , where is the adjustment sensitivity parameter, which controls the sensitivity of the trend change to the time step adjustment, is the exponent of the trend influence intensity, which optimizes the non-linear influence, is the root number of the time adjustment intensity, which is used to refine the influence of the time step adjustment, is the current time step; Evaluate the newly calculated time step and compare it with the current time step to obtain the step data for refined adjustment.

6. The planetary dynamic interaction simulation method according to claim 1, characterized in that The specific steps for merging the new data and the existing data are as follows: Based on the refined adjustment step data, collect the newly generated data at the end of the simulation cycle, and extract the data that already existed before the start of the simulation cycle; Use the formula to integrate the new data and the existing data: ， Among them, is the merging coefficient of new data, which is used to determine the weight of new data in the integration, and are adjustment parameters, which are used to optimize the non-linear influence when new data and existing data are merged, and are newly generated data and existing data respectively, is the merged data set.

7. The planetary dynamic interaction simulation method according to claim 6, wherein The specific steps for obtaining the simulation cycle comprehensive data are as follows: Analyze the newly generated data and the existing data to identify the key events and trends during the simulation cycle; Use data analysis techniques to classify and evaluate the identified events, using the formula: ， Among them, is the analysis sensitivity parameter, which is used to adjust the degree of the data analysis process, is the weighting factor, which is used to optimize the influence of the original data on the analysis result, and k is the non-linear response index, which optimizes the sensitivity of the data characteristics, is the normalization factor, is the analysis result, is the combined data set; According to the analysis results and the merged dataset , use the formula: ， Obtain comprehensive simulation cycle data , where and are weighting parameters used to adjust the influence on the data, is a normalization coefficient used to balance the proportion of the data.

8. Planetary dynamic interaction simulation system, characterized in that, Executed according to the planetary dynamic interaction simulation method described in any one of claims 1-7, the system includes: The planetary data acquisition module, based on the data input at the initial stage of simulation startup, collects the position data and velocity data of the planets, calculates the distances and relative velocities between the planets, and measures the planetary orbital parameters and gravitational fields to obtain planetary interaction characteristic data; Based on the planetary interaction feature data, the load evaluation and optimization module evaluates the computational load of the planetary interaction mechanics model, adjusts the time step of the simulation according to the calculation results, reallocates computing resources based on the adjusted time step, optimizes the processing speed, and obtains time step optimization data; Using the time step optimization data, the real-time monitoring and adjustment module monitors planetary approach events and key celestial body events, adjusts the time step according to the event occurrence frequency, refines the time granularity of the simulation, and obtains step data with refined adjustment; Based on the step data with refined adjustment, the data integration and analysis module applies incremental data integration technology to merge newly generated data in the simulation with existing data, analyzes the events within the simulation cycle, extracts key information, and obtains comprehensive simulation cycle data; According to the comprehensive simulation cycle data, the system output and log module integrates data on key celestial body events and planetary dynamic interactions, formulates simulation logs and charts, and generates planetary dynamic analysis records.

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