China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (7): 98-104.doi: 10.16265/j.cnki.issn1003-3033.2022.07.0741

• Safety engineering technology • Previous Articles     Next Articles

Investigation on back-calculation of leakage source information of gas based on modified Gaussian model

LIU Chang1(), SU Teng1, ZHOU Ru1,**(), JIANG Juncheng2   

  1. 1 College of Safety Science and Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China
    2 School of Environment & Safety Engineering, Changzhou University, Changzhou Jiangsu 213164, China
  • Received:2022-02-13 Revised:2022-04-14 Online:2022-08-12 Published:2023-01-28
  • Contact: ZHOU Ru

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)