修正高斯模型下气体泄漏源项信息反算研究

doi:10.16265/j.cnki.issn1003-3033.2022.07.0741

摘要/Abstract

摘要：

为快速准确地预测气体泄漏的强度和位置,通过耦合大气扩散模型和优化算法,建立源项信息反算模型的目标函数,基于泄漏源下风向的浓度分析计算泄漏源的位置和强度,并将混合粒子群(PSO)-差分进化(DE)算法应用到源项信息反算中,分析正向气体扩散模型对源项信息反算的影响,修正高斯烟羽模型中的烟气抬升高度,同时加入地面反射系数,并以美国空军有毒化学品扩散模型(AFTOX)模拟数据为监测泄漏浓度进行源反算,相对误差缩减至1%。结果表明:修正高斯扩散模型可验证粒子群-差分进化算法在源项信息反算中的应用;该模型在源项信息反算中的应用可有效地提高源项信息反算准确率。

关键词: 高斯烟羽模型, 气体泄漏, 源项信息反算, 粒子群(PSO)-差分进化(DE))算法, 优化算法, 美国空军有毒化学品扩散模型(AFTOX)

Abstract:

In order to quickly and accurately predict the intensity and location of gas leakage, the objective function of the source term information back-calculation model was established by coupling the atmospheric diffusion model and optimization algorithm. The location and intensity of the leakage source were calculated based on the concentration analysis of the downwind direction of the leakage source, and the hybrid PSO-DE algorithm was applied to the source information back-calculation. The influence of the forward gas diffusion model on the source term information back-calculation was analyzed, and the smoke lifting height in the Gaussian plume model was corrected. At the same time, the ground reflection coefficient is added. The source back-calculation was carried out with the simulation data of the AFTOX as the monitored leakage concentration, and the relative error was reduced to 1%. The results show that the modified Gaussian diffusion model can verify the application of particle swarm optimization-differential evolution algorithm in the back-calculation of source term information, and the application of this model in source information back-calculation can effectively improve the accuracy of source term information backcalculation

Key words: Gaussian plume model, gas leakage, investigation on back-calculation of source information, particle swarm optimization(PSO)-differential evolution(DE) algorithm, optimization algorithm, American air force toxic chemicals diffusion model (AFTOX)

刘畅, 苏腾, 周汝, 蒋军成. 修正高斯模型下气体泄漏源项信息反算研究[J]. 中国安全科学学报, 2022, 32(7): 98-104.

LIU Chang, SU Teng, ZHOU Ru, JIANG Juncheng. Investigation on back-calculation of leakage source information of gas based on modified Gaussian model[J]. China Safety Science Journal, 2022, 32(7): 98-104.

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序号	坐标	质量浓度/(mg·m^-3)
1	(280,-20,2)	282.5
2	(330,-20,2)	255.6
3	(380,-20,2)	225.3
4	(430,-20,2)	197.1
5	(480,-20,2)	172.7

参数	真实值	反算结果	相对误差
Q/(kg·s^-1)	2.00	1.999 7	0.015
x/m	-80	-80.206 8	0.258 5
y/m	20	-19.977 0	0.115

AFTOX模型		Pasquill-Gifford模式
坐标	质量浓度/(mg·m^-3)	坐标	质量浓度/(mg·m^-3)
(300,-10,2)	500	(300,-10,2)	484.2
(400,-10,2)	356	(400,-10,2)	303.2
(500,-10,2)	262	(500,-10,2)	209.4
(600,-10,2)	200	(600,-10,2)	154.5
(700,-10,2)	158	(700,-10,2)	119.6

类型	案例1	案例2	案例3	案例4
监测数据	AFTOX模型	AFTOX模型	Pasquill-Gifford模式	Pasquill-Gifford模式
源反算模型	基于修正的高斯烟羽模型	高斯烟羽模型	高斯烟羽模型	修正的高斯烟羽模型

参数	真实值	案例1		案例2		案例3		案例4
参数	真实值	结果	相对误差/%	结果	相对误差/%	结果	相对误差/%	结果	相对误差/%
Q/(kg·s^-1)	2.32	2.086 7	10.06	2.30	0.86	2.09	9.91	2.31	0.43
x/m	-50	-46.751 2	6.50	-50.46	0.92	43.72	12.56	-49.93	0.14
y/m	10	9.480 7	5.19	9.89	1.10	8.78	12.20	10.02	0.2