A method and system for simulating spatial external heat flux varying with detection frequency band

Abstract

The application provides a space external heat flow simulation method and system varying with a detection frequency band, and belongs to the field of space external heat flow simulation of gravitational wave detection satellites. Aiming at the 0.1mHz-1Hz interval of the space gravitational wave detection frequency band, a random number group conforming to the solar constant fluctuation spectrum function is generated to simulate the solar constant fluctuation sequence, and the real-time change of the solar constant fluctuation leads to the real-time change of the solar radiation external heat flow. According to the calculated solar radiation external heat flow sequence, the current of the satellite surface electric heating piece is changed, and the loading of the external heat flow varying with the detection frequency band is realized. The method solves the problem that the existing satellite and space load external heat flow simulation method cannot change with the detection frequency band, provides a space external heat flow simulation method varying with the detection frequency band, is oriented to low-frequency space gravitational wave detection application, can accurately simulate the change of the low-frequency solar radiation external heat flow in the 0.1mHz-1Hz interval, and is high in accuracy and easy to implement in engineering.

Description

Technical Field

[0001] This invention belongs to the field of thermal control and relates to a method for simulating external space heat flow that varies with the detection frequency band. Background Technology

[0002] Space heat flux refers to the various space radiation heat sources that reach the outer surface of a satellite while it is orbiting in outer space. Changes in external heat flux cause temperature fluctuations in the satellite's internal payloads and critical components. This is a factor that needs to be studied in detail during the design and development phase of satellites and payloads, and serves as the basis for space environment adaptability studies and thermal design. The thermal design of satellites and payloads needs to be verified through thermal balance tests on the ground, and space heat flux simulation is an important test condition for these tests. Since space heat flux changes continuously over time during on-orbit operation, the accuracy of space heat flux simulation has a significant impact on the correctness of the thermal balance test results. Currently, most satellite and payload heat flux analyses treat external heat flux as a dynamic quantity that changes with the satellite's orbit, attitude, and shape, but neglect the fluctuations in the detection frequency of external heat flux.

[0003] Gravitational wave detection is frequency-dependent. Space-based gravitational wave detection payloads are primarily used to detect gravitational waves in the mHz–Hz frequency band, and can be applied to observations of massive astronomical events such as the collision and merger of binary black holes and binary neutron stars. The European Space Agency (ESA) proposed the LISA project in 1990. Domestically, the Tianqin project was proposed in 2014, and the Taiji project in 2016. Due to the ultra-high sensitivity requirements of gravitational wave detection, stringent requirements are placed on the temperature stability of key internal components of the satellite and payload, especially considering the impact of temperature fluctuations in the mHz–Hz frequency band. The low-frequency range for space-based gravitational wave detection needs to reach 0.1 mHz. Although the changes in solar external heat flow caused by orbital motion are large, their impact on temperature fluctuations in the mHz–Hz frequency band is relatively small. For heliocentric orbit gravitational wave detection schemes such as LISA and Taiji, solar heat flow is the main influencing factor, and the changes in the mHz–Hz frequency band mainly come from fluctuations in the solar constant. The fluctuation of the solar constant ΔS(f) is expressed using the spectral function of the solar constant fluctuation. The term is used to describe the process, where f represents the detection frequency, typically between 0.1 mHz and 1 Hz, and S is the solar constant. The lower the detection frequency, the greater the impact of solar fluctuations on the system. At 0.1 mHz, the fluctuation introduced by ΔS(f) is approximately 0.3%, affecting the temperature fluctuations of key components within the satellite and payload. Since the changes in solar heat flow in current thermal outflow simulations do not change with the detection frequency, simulations of solar constant fluctuations with varying detection frequency are needed to account for these fluctuations during the thermal equilibrium phase for gravitational wave detection payloads.

[0004] Most of the current technical achievements simulate the magnitude of external heat flux based on orbit and attitude, and do not involve the simulation of external heat flux fluctuations related to detection frequency. Contents of the Invention

[0005] The technical problem solved by the present invention is: overcoming the deficiencies of the prior art, providing a space external heat flux simulation method and system that varies with the detection frequency band, solving the problem that the existing external heat flux simulation methods for satellites and space loads cannot vary with the detection frequency band, and providing a space external heat flux simulation method that varies with the detection frequency band. Oriented to low-frequency space gravitational wave detection applications, it can accurately simulate the variation of low-frequency solar radiation external heat flux in the range of 0.1mHz to 1Hz, with high accuracy and easy engineering implementation.;

[0006] The technical solution of the present invention is: a space external heat flux simulation method varying with detection frequency band, comprising:

[0007] According to the detection frequency band requirement interval [f1,f N , an N×1 equally-spaced increasing sequence {f i}, i=1,2,…,N, wherein f1 is a positive real number and is the minimum value in the detection frequency band requirement interval, f N is a positive real number and is the maximum value in the detection frequency band requirement interval, and N is a positive integer;

[0008] setting an N×1 equally-spaced increasing time sequence {t k}, k=1,2,…,N; let t1=0, t k =(k-1)×Δt; T=t N is counted as 1 timing cycle;

[0009] According to the observation time length requirement of the thermal environment test, the total observation time T tot is divided into M timing cycles, the time length of each timing cycle is T=t N , and any part less than one timing cycle is counted as one timing cycle; then T tot =(M-1)t N +(p-1)Δt, where M and p are positive integers and p<N; M random numbers are generated respectively for the M timing cycles, denoted as η j , j=1,2,…,M; and η j is a uniformly distributed random number in the interval [0,1];

[0010] sequentially generating the solar constant fluctuation sequence Δs(t tot ) corresponding to the observation time of length T j,k , where t j,k ∈[0,T tot represents the k-th observation moment in the j-th timing cycle in the observation time sequence, and t j,k=(j-1)T+(k-1)Δt,j=1,2,…,M,k=1,2,…N;

[0011] Based on the observation time requirements of the thermal environment experiment, the input value of the solar constant fluctuation, real(Δs(t), is used. j,k )) and the average solar radiation intensity S j Merged into a solar constant sequence S j +real(Δs(t j,k ));

[0012] The orbit was set using thermal analysis software, the six orbital elements and the solar constant sequence were input, a satellite external structure model was established, the external heat flow reached by the satellite in various directions under different operating conditions was calculated and analyzed, and the heat flow was loaded onto the satellite in chronological order.

[0013] Arithmetic increasing sequence {f i In}, the frequency difference between two adjacent frequencies is (f N -f1) / N.

[0014] Arithmetic increasing time series {t k In the equation, the time difference Δt between two adjacent times is 1 / f. N .

[0015] Solar constant fluctuation sequence Δs(t) j,k The specific steps involved in generating this process include:

[0016] Based on the satellite orbit and the angle β between the solar vector and the satellite orbital plane, determine the average solar radiation intensity S in the solar irradiation area. j j = 1, 2, ..., M;

[0017] t was calculated j,k Fluctuations in the solar constant at time:

[0018]

[0019] Wherein, Δs(t) j,k Take the real part real(Δs(t) j,k As t j,k The input value for the fluctuation of the solar constant at time t.

[0020] The loading is carried out on the satellite in chronological order. Specifically, the loading method involves changing the current of the heating plate attached to the solar radiation region of the satellite according to the magnitude of the solar radiation external heat flow sequence. The current is updated every Δt time interval, thereby simulating the solar radiation external heat flow in a specific detection frequency range.

[0021] A space external heat flow simulation system that varies with the detection frequency band includes:

[0022] A first module, which is configured to generate an N×1 arithmetic increment sequence {f N} according to the required detection frequency band interval [f1,f i}, where i=1,2,…,N, f1 is a positive real number and is the minimum value in the required detection frequency band interval, f N N is a positive real number and is the maximum value in the required detection frequency band interval, and N is a positive integer;

[0023] A second module, which is configured to set an N×1 arithmetic increment time sequence {t k}, where k=1,2,…,N; t1=0 is set, t k =(k-1)×Δt; T=t N is counted as one timing cycle;

[0024] A third module, which is configured to divide the total observation time T tot into M timing cycles according to the observation time length requirement of the thermal environment test, wherein the time length of each timing cycle is T=t N , and any part less than one timing cycle is counted as one timing cycle; then T tot =(M-1)t N +(p-1)Δt, M and p are positive integers and p<N; M random numbers are respectively generated for the M timing cycles, marked as η j , where j=1,2,…,M; η j j is a uniformly distributed random number within the interval [0,1];

[0025] A fourth module, which sequentially generates a solar constant fluctuation sequence Δs(t tot ) corresponding to the observation time of length T j,k , where t j,k ∈[0,T tot represents the k-th observation moment within the j-th timing cycle in the observation time sequence, and t j,k =(j-1)T+(k-1)Δt,j=1,2,…,M,k=1,2,…N;

[0026] A fifth module, which combines the input value real(Δs(t j,k )) of solar constant fluctuation with the average solar radiation intensity S j into a solar constant sequence S j +real(Δs(t j,k )) according to the observation time requirement of the thermal environment test;

[0027] A sixth module, which adopts thermal analysis software to set an orbit, inputs six orbital elements and the solar constant sequence, establishes a satellite external structure model, calculates and analyzes the external heat flow reached in all directions of the satellite under different working conditions, and loads the heat flow onto the satellite in chronological order.

[0028] Arithmetic increasing sequence {f i In}, the frequency difference between two adjacent frequencies is (f N -f1) / N.

[0029] Arithmetic increasing time series {t k In the equation, the time difference Δt between two adjacent times is 1 / f. N .

[0030] Solar constant fluctuation sequence Δs(t) j,k The specific steps involved in generating this process include:

[0031] Based on the satellite orbit and the angle β between the solar vector and the satellite orbital plane, determine the average solar radiation intensity S in the solar irradiation area. j j = 1, 2, ..., M;

[0032] t was calculated j,k Fluctuations in the solar constant at time:

[0033]

[0034] Wherein, Δs(t) j,k Take the real part real(Δs(t) j,k As t j,k The input value for the fluctuation of the solar constant at time t.

[0035] The loading is carried out on the satellite in chronological order. Specifically, the loading method involves changing the current of the heating plate attached to the solar radiation region of the satellite according to the magnitude of the solar radiation external heat flow sequence. The current is updated every Δt time interval, thereby simulating the solar radiation external heat flow in a specific detection frequency range.

[0036] The advantages of this invention compared to the prior art are:

[0037] (1) Compared with existing space heat flow simulation methods, this invention considers the heat flow simulation situation related to the detection frequency and proposes a method and system for generating a random sequence of solar constant fluctuations. The corresponding solar radiation heat flow sequence is calculated based on the random sequence of solar constant fluctuations and loaded onto the satellite by changing the current of the heating plate. This method can effectively target application fields that are sensitive to the detection frequency, such as gravitational wave detection.

[0038] (2) Compared with existing methods for simulating extraterrestrial heat flow, existing methods often ignore the fluctuations of the solar constant, treating it as a constant or slowly varying value, with a minimum time resolution of more than 6 hours. The time interval of the random sequence of solar constant fluctuations generated by this invention is determined by the reciprocal of the maximum detection frequency band. For the detection frequency band of 0.1 mHz to 1 Hz, the minimum time resolution of the solar constant reaches 1 second. Furthermore, the method of changing the current magnitude is used to load the satellite, fully simulating the fluctuation process of the solar constant. Attached Figure Description

[0039] Figure 1 This is a flowchart of the method of the present invention.

[0040] Figure 2 It is the random sequence of solar constant fluctuations generated by the method of this invention.

[0041] Figure 3 It is the statistical result of the spectral function of the random sequence of solar constant fluctuations generated by the method of this invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0043] Example 1:

[0044] This invention proposes a method for simulating external heat flow in space that varies with the detection frequency band. For the space gravitational wave detection frequency band of 0.1 mHz to 1 Hz, a solar constant fluctuation sequence conforming to a certain spectral function is generated, and then the corresponding solar radiation external heat flow sequence is calculated as the basis for loading solar radiation external heat flow onto the satellite surface. The flowchart of this invention is shown below. Figure 1 As shown.

[0045] Step 1: Based on the required frequency band [f1, f N Let N×1 be an arithmetic progression {f}. i}, i=1,2,…,N, and the frequency difference between two adjacent frequencies is (f N -f1) / N. Based on the detection requirements of space gravitational waves in the detection frequency band of 0.1mHz to 1Hz, preferably, f1 = 0.1mHz, f N =1Hz, N=10000. {f i} is an arithmetic progression, and the frequency difference between two adjacent frequencies is Δf = 0.1 mHz.

[0046] Step 2, set an N×1 time arithmetic sequence {t} k}, k = 1, 2, ..., N, and the time difference Δt between two adjacent times is 1 / f N; let t1=0, t k =(k-1)×Δt. T=t N is counted as 1 timing cycle. According to the detection requirement of space gravitational waves for the detection frequency band of 0.1mHz to 1Hz, preferably, t1=0, Δt=1s, t N =10000s, N=10000, and T=10000s is counted as 1 timing cycle.

[0047] Step 3, according to the observation time length requirement of the thermal environment test, the total observation time T tot is divided into M timing cycles, and the time length of each timing cycle is T=t N , and any part less than one timing cycle is counted as one timing cycle; T tot =(M-1)t N +(p-1)Δt, where M and p are positive integers and p<N; M random numbers are respectively generated for M timing cycles, denoted as η j , j=1,2,…,M; then η j is a random number uniformly distributed in the interval [0,1];

[0048] Step 4,

[0049] sequentially generate the solar constant fluctuation sequence Δs(t tot ) corresponding to the observation time of T j,k length, wherein t j,k ∈[0,T tot is the k-th observation time in the j-th timing cycle in the observation time sequence, and t j,k =(j-1)T+(k-1)Δt, j=1,2,…,M, k=1,2,…N.

[0050] The specific steps for generating the solar constant fluctuation sequence Δs(t j,k ) are as follows:

[0051] First step, according to the sun-earth distance and the sunspot activity cycle, determine the average value S of the solar constant at time t j,k , j=1,2…,M; S j is a constant value within the j-th timing cycle. j is a constant value within the j-th timing cycle.

[0052] Second step, calculate the solar constant fluctuation at time t j,k

[0053]

[0054] wherein, the real part real(Δs(t j,k )) is taken as t j,k as t j,k ​The input value for the fluctuation of the solar constant at time t;

[0055] Step 5: Based on the observation time requirements of the thermal environment experiment, input the solar constant fluctuation value real(Δs(t)). j,k )) and the average value of the solar constant S j Merged into a solar constant sequence S j +real(Δs(t j,k )).

[0056] Step 6: Use thermal analysis software to set the orbit, input the six orbital elements and the solar constant sequence, establish the satellite's external structure model, and calculate and analyze the external heat flow reached by the satellite in various directions under different operating conditions.

[0057] The heat is applied to the satellite in chronological order. Specifically, a thin-film polyimide heating element is attached to the area where external heat flow needs to be simulated. A programmable power supply controls the current to the heating element to change the applied heat. The current value is adjusted over time to simulate the external heat flow of solar radiation within a specific detection frequency range.

[0058] The method of this invention generates multiple random sequences of solar constant fluctuations. Figure 2 Four sets of random sequences are shown: real(s(t)) / (1.3×10⁻⁶). -4 The result of S) corresponds to an observation duration of 1 counting cycle. Figure 3 This shows the spectrum of solar constant fluctuations obtained by averaging ten random sequences and performing a Fourier transform, and comparing it with the spectrum of the solar constant to be simulated (f). i / Hz) -1 / 3 The spectral curves are consistent.

[0059] Furthermore, the present invention also relates to a space external heat flow simulation system that varies with the detection frequency band, comprising:

[0060] The first module, based on the required frequency band range [f1, f...], N Let N×1 be an arithmetic progression {f}. i}, i = 1, 2, ..., N, f1 is a positive real number and is the minimum value in the required frequency band range, f N N is a positive real number and is the maximum value in the required frequency band range for the detection band; N is a positive integer.

[0061] The second module sets up an N×1 arithmetic progression time series {t}. k}, k = 1, 2, ..., N; let t1 = 0, t k = (k-1)×Δt; T = t N This is counted as one timing cycle;

[0062] The third module, which divides the total observation time T tot into M timing cycles according to the observation duration requirement of the thermal environment test, wherein the duration of each timing cycle is T=t N , and any part less than one timing cycle is counted as one timing cycle; then T tot =(M-1)t N +(p-1)Δt, wherein M and p are positive integers and p<N; M random numbers are generated respectively for the M timing cycles, recorded as η j , j=1,2,…,M; then η j is a random number uniformly distributed in the interval [0,1];

[0063] The fourth module sequentially generates the solar constant fluctuation sequence Δs(t tot ) corresponding to the observation time of T j,k length, wherein t j,k ∈[0,T tot represents the k-th observation moment within the j-th timing cycle in the observation time sequence, and t j,k =(j-1)T+(k-1)Δt, j=1,2,…,M,k=1,2,…N;

[0064] The fifth module combines the input value real(Δs(t j,k )) of solar constant fluctuation with the average solar radiation intensity S j into a solar constant sequence S j +real(Δs(t j,k )) according to the observation time requirement of the thermal environment test;

[0065] The sixth module adopts thermal analysis software to set the orbit, input six orbital elements and the solar constant sequence, establish a satellite external structure model, calculate and analyze the external heat flow reached in all directions of the satellite under different working conditions, and load the heat flow onto the satellite in chronological order.

[0066] Although the present invention has been disclosed as above in the form of preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make possible changes and modifications to the technical solution of the present invention by using the above disclosed technical content without departing from the spirit and scope of the present invention. Therefore, all simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for simulating external space heat flow that varies with the detection frequency band, characterized in that, include: Based on the required frequency band range [ , Let N×1 be an arithmetic progression. }, i=1,2,…,N, It is a positive real number and is the minimum value in the required frequency band range. N is a positive real number and is the maximum value in the required frequency band range for the detection band; N is a positive integer. Set an N×1 arithmetic progression time series { }, k=1,2,…,N; Let , ; This is counted as one timing cycle; According to the requirement for the observation duration in thermal environment test, the total observation time is divided into M timing cycles, and the duration of each timing cycle is , and any portion less than one timing cycle is counted as one timing cycle; then , M and p are positive integers and p<N; M random numbers are respectively generated in M timing cycles, denoted as , j=1,2,…,M; then is a random number uniformly distributed within the interval [0,1]; Produced in sequence Solar constant fluctuation sequence corresponding to the length of observation time ,in Let represent the k-th observation time within the j-th timing period of the observation time series, and , j=1,2,…,M, k=1,2,…N; Based on the observation time requirements of the thermal environment test, the input value of the solar constant fluctuation is real( (and the average solar radiation intensity) Merged into a solar constant sequence +real( ); The orbit was set using thermal analysis software, the six orbital elements and the solar constant sequence were input, a satellite external structure model was established, the external heat flow reached by the satellite in various directions under different operating conditions was calculated and analyzed, and the heat flow was loaded onto the satellite in chronological order.

2. The method for simulating external space heat flow varying with the detection frequency band according to claim 1, characterized in that, Arithmetic increasing sequence { In the context of}, the frequency difference between two adjacent frequencies is . .

3. The method for simulating external space heat flow varying with the detection frequency band according to claim 1, characterized in that, Arithmetic increasing time series { In the context of time difference between two adjacent times, ... for .

4. The method for simulating external space heat flow varying with the detection frequency band according to claim 1, characterized in that, Solar constant fluctuation sequence The specific steps involved in generating the product include: The average solar radiation intensity of the solar irradiation area is determined based on the satellite orbit and the angle β between the solar vector and the satellite orbital plane. j=1,2,…,M; Calculated Fluctuations in the solar constant at time: in, Take the real part (real) As The input value for the fluctuation of the solar constant at time t.

5. The method for simulating external space heat flow varying with the detection frequency band according to claim 1, characterized in that, The heating elements are loaded onto the satellite in chronological order. Specifically, the loading method involves adjusting the current of the heating element attached to the satellite's solar radiation region based on the magnitude of the external heat flux sequence caused by solar radiation. The current is adjusted according to the time interval... The time is updated once, thus enabling the simulation of solar radiation external heat flow within a specific detection frequency range.

6. A space external heat flow simulation system that varies with the detection frequency band, characterized in that, include: The first module, based on the required frequency band range for detection... , Let N×1 be an arithmetic progression. }, i=1,2,…,N, It is a positive real number and is the minimum value in the required frequency band range. N is a positive real number and is the maximum value in the required frequency band range for the detection band; N is a positive integer. The second module sets up an N×1 arithmetic progression time series { }, k=1,2,…,N; Let , ; This is counted as one timing cycle; The third module, in view of the requirement for the observation time length of the thermal environment test, the total observation time is divided into M timing cycles, and the time length of each timing cycle is , and any part less than one timing cycle is counted as one timing cycle; then , M and p are positive integers and p<N; M random numbers are respectively generated in the M timing cycles, denoted as , j=1,2,…,M; then is a random number uniformly distributed within the interval [0,1]; The fourth module generates sequentially. Solar constant fluctuation sequence corresponding to the length of observation time ,in Let represent the k-th observation time within the j-th timing period of the observation time series, and , j=1,2,…,M, k=1,2,…N; The fifth module, based on the observation time requirements of the thermal environment experiment, inputs the solar constant fluctuation value real( (and the average solar radiation intensity) Merged into a solar constant sequence +real( ); The sixth module uses thermal analysis software to set the orbit, input the six orbital elements and the solar constant sequence, establish a satellite external structure model, calculate and analyze the external heat flow reached by the satellite in various directions under different operating conditions, and load it onto the satellite in chronological order.

7. A space external heat flow simulation system varying with the detection frequency band according to claim 6, characterized in that, Arithmetic increasing sequence { In the context of}, the frequency difference between two adjacent frequencies is . .

8. A space external heat flow simulation system varying with the detection frequency band according to claim 6, characterized in that, Arithmetic increasing time series { In the context of time difference between two adjacent times, ... for .

9. A space external heat flow simulation system varying with the detection frequency band according to claim 6, characterized in that, Solar constant fluctuation sequence The specific steps involved in generating the product include: The average solar radiation intensity of the solar irradiation area is determined based on the satellite orbit and the angle β between the solar vector and the satellite orbital plane. j=1,2,…,M; Calculated Fluctuations in the solar constant at time: ； in, Take the real part (real) As The input value for the fluctuation of the solar constant at time t.

10. A space external heat flow simulation system varying with the detection frequency band according to claim 6, characterized in that, The heating elements are loaded onto the satellite in chronological order. Specifically, the loading method involves adjusting the current of the heating element attached to the satellite's solar radiation region based on the magnitude of the external heat flux sequence caused by solar radiation. The current is adjusted according to the time interval... The time is updated once, thus enabling the simulation of solar radiation external heat flow within a specific detection frequency range.

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