Space gravitational wave detection parameter management and performance analysis based on MBSE

doi:10.11996/JG.j.2095-302X.2024020259

Abstract

Abstract:

In order to dynamically associate the decomposition of top-level parameters with the analysis of system-level performance in the space gravitational wave detection system, and to provide management and application analysis capabilities for the entire lifecycle information of space science tasks, a model-based system engineering (MBSE) method for managing parameters and analyzing detection performance in space gravitational wave detection systems was proposed. Parameter models for space gravitational wave detectors were constructed using the system modeling language (SysML), enabling the analysis of model content and recording of parameters after screening. Finally, an analysis was conducted on the detection performance of the space gravitational wave detection system for different scientific targets through detection sensitivity, which served as the main criterion for evaluating the detection ability of the system. The results demonstrated that the proposed method can enable the uniform management and tracing of all parameter contents, thereby supporting the demonstration of top-level parameters and the evaluation of system-level performance in the space gravitational wave detection system.

Key words: MBSE, SysML, model analysis, gravitational waves, detection sensitivity

CLC Number:

TP391

ZHU Yiming, ZHANG Yuzhu, CHEN Bin, PENG Xiaodong, GAO Chen, LIU Yu, TANG Wenlin, QIANG Li’e, XU Peng, LUO Ziren. Space gravitational wave detection parameter management and performance analysis based on MBSE[J]. Journal of Graphics, 2024, 45(2): 259-267.

Figures/Tables 11

References 28

[1]	WEINBERG S. Principles and applications of the general theory of relativity[J]. Gravitation and Cosmology, 1972, 25(2): 65-65.
[2]	DANZMANN K, PRINCE T. LISA assessment studyreport (yellow book)[R]. Paris: European Space Agency, 2011.
[3]	LUO J, CHEN L S, DUAN H Z, et al. TianQin: a space-borne gravitational wave detector[J]. Classical & Quantum Gravity, 2016, 33(3): 035010.
[4]	HU W R, WU Y L. The Taiji program in space for gravitational wave physics and the nature of gravity[J]. National Science Review, 2017, 4(5): 685-686. DOI URL
[5]	BENDER P L. Additional astrophysical objectives for LISA follow-on missions[J]. Classical and Quantum Gravity, 2004, 21(5): S1203-S1208.
[6]	KAWAMURA S, ANDO M, SETO N, et al. The Japanese space gravitational wave antenna: DECIGO[J]. Classical & Quantum Gravity, 2011, 28(9): 094011.
[7]	HISCOCK B, HELLINGS R W. OMEGA: a space gravitational wave MIDEX mission[C]// The 191st AAS Meeting. Washington: Astronomical Society, 1997, 29: 1312.
[8]	罗子人, 白姗, 边星, 等. 空间激光干涉引力波探测[J]. 力学进展, 2013, 43(4): 415-447.
	LUO Z R, BAI S, BIAN X, et al. Gravitational wave detection by space laser interferometry[J]. Advances in Mechanics, 2013, 43(4): 415-447 (in Chinese).
[9]	LARSON S L, HISCOCK W A, HELLINGS R W. Sensitivity curves for spaceborne gravitational wave interferometers[J]. Physical Review D, 2000, 62(6): 062001. DOI URL
[10]	焦洪臣, 雷勇, 张宏宇, 等. 基于MBSE的航天器系统建模分析与设计研制方法探索[J]. 系统工程与电子技术, 2021, 43(9): 2516-2525. DOI
	JIAO H C, LEI Y, ZHANG H Y, et al. Research on modeling and design method of spacecraft system based on MBSE[J]. Systems Engineering and Electronics, 2021, 43(9): 2516-2525 (in Chinese). DOI
[11]	王国梁, 赵滟, 卢志昂, 等. 基于MBSE的导弹武器系统效能评估[J]. 火力与指挥控制, 2022, 47(8): 116-123, 131.
	WANG G L, ZHAO Y, LU Z A, et al. Effectiveness evaluation of missile weapon system based on MBSE[J]. Fire Control & Command Control, 2022, 47(8): 116-123, 131 (in Chinese).
[12]	WYMORE A W. Model-based systems engineering[M]. Boca Raton: CRC Press, 2013: 201-205.
[13]	HIRSHORN S R. Expanded guidance for nasa systems engineering. volume 2: crosscutting topics, special topics, and appendices[R]. Washington: National Aeronautics and Space Administration, 2016.
[14]	关锋, 葛平, 周国栋, 等. MBSE发展趋势与中国探月工程并行协同论证[J]. 空间科学学报, 2022, 42(2): 183-190.
	GUAN F, GE P, ZHOU G D, et al. Development trend of MBSE and investigation of concurrent collaborative demonstration for Chinese lunar exploration program[J]. Chinese Journal of Space Science, 2022, 42(2): 183-190 (in Chinese). DOI URL
[15]	徐德胜, 高倩, 胡士强, 等. 基于SysML与Simulink的飞机供电系统联合仿真研究[C]// 第五届中国航空科学技术大会. 北京: 北京航空航天大学出版社, 2021: 500-504.
	XU D S, GAO Q, HU S Q, et al. Research on co-simulation of aircraft electrical power system based on SysML and Simulink[C]// The 5th Chinese Aeronautics Science and Technology Conference. Beijing: Beihang University Press, 2021: 500-504 (in Chinese).
[16]	李新光, 刘继红. 基于SysML的系统设计-仿真模型可视化转换[J]. 计算机辅助设计与图形学学报, 2016, 28(11): 1973-1981.
	LI X G, LIU J H. A method of sys ML-based visual transformation of system design-simulation models[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(11): 1973-1981 (in Chinese).
[17]	王宗仁, 周苏闰, 王丕东, 等. 基于MBSE的卫星产品系统与可靠性集成设计技术研究[C]// 第三届体系工程学术会议——复杂系统与体系工程管理. 武汉: 中科蓬勃出版社有限公司武汉编辑部, 2021: 385-394.
	WANG Z R, ZHOU S R, WANG P D, et al. Research on integration design technology of satellite system and reliability based on MBSE[C]// The 3th Academic Conference on System Engineering - Complex Systems and System Engineering Management. Wuhan: China Schience Boom Press Limiten, 2021: 385-394 (in Chinese).
[18]	PAREDIS C J J, JOHNSON T. Using OMG’S SysML to support simulation[C]// 2008 Winter Simulation Conference. New York: IEEE Press, 2008: 2350-2352.
[19]	CAO Y, LIU Y S, FAN H R, et al. SysML-based uniform behavior modeling and automated mapping of design and simulation model for complex mechatronics[J]. Computer- Aided Design, 2013, 45(3): 764-776. DOI URL
[20]	JOHNSON T, KERZHNER A, PAREDIS C J J, et al. Integrating models and simulations of continuous dynamics into SysML[J]. Journal of Computing and Information Science in Engineering, 2012, 12(1): 1.
[21]	FRIEDENTHAL S, MOORE A, STEINER R. A practical guide to SysML: the systems modeling language[M]. Third edition. Waltham, MA: Elsevier/Morgan Kaufmann, 2015: 107-110.
[22]	张玉金, 黄博, 廖文和. 面向场景的航空发动机基于模型的系统工程设计[J]. 计算机集成制造系统, 2021, 27(11): 3093-3102. DOI
	ZHANG Y J, HUANG B, LIAO W H. MBSE unified modeling and design method of commercial aeroengine for operation scenario[J]. Computer Integrated Manufacturing Systems, 2021, 27(11): 3093-3102 (in Chinese).
[23]	LU X Y, TAN Y J, SHAO C G. Sensitivity functions for space-borne gravitational wave detectors[J]. Physical Review D, 2019, 100(4): 044042. DOI URL
[24]	LUO Z R, WANG Y, WU Y L, et al. The Taiji program: a concise overview[J]. Progress of Theoretical and Experimental Physics, 2021, 2021(5): 05A108. DOI URL
[25]	BROWN W R, KILIC M, HERMES J J, et al. A 12 minute orbital period detached white dwarf eclipsing binary[J]. The Astrophysical Journal Letters, 2011, 737(1): L23. DOI URL
[26]	KILI M, BROWN W R, GIANNINAS A, et al. A new gravitational wave verification source[J]. Monthly Notices of the Royal Astronomical Society: Letters, 2014, 444(1): L1-L5. DOI URL
[27]	ROBSON T, CORNISH N J, LIU C. The construction and use of LISA sensitivity curves[J]. Classical & Quantum Gravity, 2019, 36(10): 105011.
[28]	AJITH P, BABAK S, CHEN Y, et al. A phenomenological template family for black-hole coalescence waveforms[J]. Classical & Quantum Gravity, 2007, 24(19): S689-S699.

标签名	含义	关键属性
<packagedElement>	元素定义标签。所有参数指标的名称和唯一标识符通过该标签记录	name名称； xmi:id 唯一标识符
<ownedAttribute>	特征属性标签。记录Block的特征属性。指标值和指标之间的层级关系通过该标签记录	name名称； type 组成属性所属的Block唯一标识符
<sysml:Block>	模块标签。记录所有指标参数的唯一标识符，用于定位对应的元素定义标签	base_Class引用元素的唯一标识符
<defaultValue>	值属性默认值标签。指标参数分配的指标值和对应单位通过该标签记录	xmi:type单位； value指标值

标签名	含义	关键属性
<packagedElement>	元素定义标签。所有参数指标的名称和唯一标识符通过该标签记录	name名称； xmi:id 唯一标识符
<ownedAttribute>	特征属性标签。记录Block的特征属性。指标值和指标之间的层级关系通过该标签记录	name名称； type 组成属性所属的Block唯一标识符
<sysml:Block>	模块标签。记录所有指标参数的唯一标识符，用于定位对应的元素定义标签	base_Class引用元素的唯一标识符
<defaultValue>	值属性默认值标签。指标参数分配的指标值和对应单位通过该标签记录	xmi:type单位； value指标值

转移频率	a_k	b_k	c_k
f₀	2.974 0×10^-1	4.481 0×10^-2	9.556 0×10^-2
f₁	5.941 1×10^-1	8.979 4×10^-2	1.911 1×10^-1
f₂	5.080 1×10^-1	7.751 5×10^-2	2.236 9×10^-2
f₃	8.484 5×10^-1	1.284 8×10^-1	2.729 9×10^-1

转移频率	a_k	b_k	c_k
f₀	2.974 0×10^-1	4.481 0×10^-2	9.556 0×10^-2
f₁	5.941 1×10^-1	8.979 4×10^-2	1.911 1×10^-1
f₂	5.080 1×10^-1	7.751 5×10^-2	2.236 9×10^-2
f₃	8.484 5×10^-1	1.284 8×10^-1	2.729 9×10^-1