GA-PS Based Three-dimensional Space Source Inversion Algorithm

doi:10.12382/bgxb.2022.0272

Abstract

Abstract:

In response to the current dominance of hazard source location and source intensity inverse calculation in chemical hazards being confined to the two-dimensional plane, this study focuses on high-dimensional source inversion optimization characteristics. To address this limitation, we propose the Modified Genetic Algorithm and Pattern Search algorithm based on Genetic Algorithm-Pattern Search Algorithm, utilizing genetic algorithms for global optimization and leveraging the pattern search algorithm’s local optimization performance. The simulation results show that the algorithm can realize the three-dimensional spatial location of the hazard source and the inverse calculation of the source intensity using the concentration data of hazardous substances from a group of ground or air detectors in the three-dimensional space. Through inverse calculation of the measured data of the SF6 field experiment, it is verified that the algorithm can realize effective inverse calculation of the spatial location and source intensity of the hazard source under stable atmospheric conditions, achieving an inverse calculation accuracy within 30%.

Key words: chemical hazard, three-dimensional space, genetic algorithm, pattern search algorithm, source inversion

CLC Number:

E91
X928.5

CHEN Song, ZHU Dongsheng, ZUO Qinwen, HAN Chaoshuai. GA-PS Based Three-dimensional Space Source Inversion Algorithm[J]. Acta Armamentarii, 2023, 44(8): 2503-2520.

Figures/Tables 36

References 28

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方向	扩散方程	大气稳定度	γ	μ	下风距离/m
y	σ_y=γx^μ	D级	0.110726	0.929418	1~1000
			0.146669	0.888723	>1000
z	σ_z=γx^μ	D级	0.104634	0.826212	1~1000
			0.400167	0.632023	>1000

方向	扩散方程	大气稳定度	γ	μ	下风距离/m
y	σ_y=γx^μ	D级	0.110726	0.929418	1~1000
			0.146669	0.888723	>1000
z	σ_z=γx^μ	D级	0.104634	0.826212	1~1000
			0.400167	0.632023	>1000

y/m	x/m
y/m	250	500	750	1000	1250
100	31.95802862	387.08525	367.6454777	278.3340544	90.40847051
60	630.7893626	1121.3852	594.006858	366.1385291	261.0453579
20	575.6576425	773.066851	416.7973147	333.6252268	245.2681073
-20	0.416086777	36.60284873	227.8322835	209.8455332	181.8178239
-60	9.57555×10^-7	5.634278715	53.85226113	92.8115419	105.2333203
-100	6.8812×10^-15	0.057732329	6.802763206	13.05211306	47.75791929

y/m	x/m
y/m	250	500	750	1000	1250
100	31.95802862	387.08525	367.6454777	278.3340544	90.40847051
60	630.7893626	1121.3852	594.006858	366.1385291	261.0453579
20	575.6576425	773.066851	416.7973147	333.6252268	245.2681073
-20	0.416086777	36.60284873	227.8322835	209.8455332	181.8178239
-60	9.57555×10^-7	5.634278715	53.85226113	92.8115419	105.2333203
-100	6.8812×10^-15	0.057732329	6.802763206	13.05211306	47.75791929

运行次数	x/m	y/m	He/m	Q/(g·s^-1)	耗时/s	x相对误差/10^-4	Q相对误差/10^-5
1	30.01	50.00	10.00	4999783.77	236.204	3.33	4.32
2	29.99	50.00	10.00	5000205.93	238.033	3.33	4.12
3	30.01	50.00	10.00	4999787.93	270.030	3.33	4.24
4	30.01	50.00	10.00	4999782.37	201.632	3.33	4.35
5	30.01	50.00	10.00	4999769.90	264.663	3.33	4.60
6	30.01	50.00	10.00	4999820.43	177.936	3.33	3.59
7	30.01	50.00	10.00	4999805.10	279.241	3.33	3.90
8	30.01	50.00	10.00	4999780.06	264.850	3.33	4.40
9	29.99	50.00	10.00	5000217.31	190.394	3.33	4.35
10	30.01	50.00	10.00	4999758.12	323.281	3.33	4.84