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Source strength inversion of PSO-IA under modified Gaussian models
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Bangyin WAN1, 2, Niansheng KUAI2, **, Xiongyuan HE3, Minjun PENG3, Limin DENG2
China Safety Science Journal | 2024, 34(7) : 132 - 138
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China Safety Science Journal | 2024, 34(7): 132-138
• Safety engineering technology •
Source strength inversion of PSO-IA under modified Gaussian models
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Bangyin WAN1, 2, Niansheng KUAI2, **, Xiongyuan HE3, Minjun PENG3, Limin DENG2
Affiliations
  • 1 School of Environment and Resources，Southwest University of Science and Technology，Mianyang Sichuan 621010，China
  • 2 Sichuan Institute of Safety Science and Technology，Chengdu Sichuan 610045，China
  • 3 Sichuan Key Laboratory of Measurement and Control of Major Hazardous Sources，Chengdu Sichuan 610045，China
Published: 2024-07-28 doi: 10.16265/j.cnki.issn1003-3033.2024.07.0146
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In order to improve the science and effectiveness of traceability and localization of hazardous gas leaks，determining the location and intensity of dangerous gas leaks is the key to emergency response to accidents. The Gaussian plume model was modified by analyzing the mass conservation law and improving the diffusion amplitude of the gas plume with an approximate Gaussian distribution. Additionally，a heuristic algorithm based on the principle of immunization—IA coupled with PSO—was proposed，and the PSO-IA algorithm was applied to source strength inversion. It is concluded that the modified Gaussian plume model has been verified by three classical algorithms (PS，GA and PSO)，resulting in a prediction value error decreased by about 2%. PSO algorithm，which showed a better inversion effect，was selected for comparison with the PSO-IA algorithm. The PSO-IA algorithm has improved the effect of inverting source strength，with a localization error is 1.3 m，a source strength solving error of 0.8%，and a single computation time of less than 1 second. This enables fast and accurate positioning and estimation of source strength.

particle swarm optimization-immune algorithm(PSO-IA)  /  modified Gaussian smoke plume model  /  source-strength inversion  /  hazardous gas leakage  /  solving accuracy
Bangyin WAN, Niansheng KUAI, Xiongyuan HE, Minjun PENG, Limin DENG. Source strength inversion of PSO-IA under modified Gaussian models[J]. China Safety Science Journal, 2024 , 34 (7) : 132 -138 . DOI: 10.16265/j.cnki.issn1003-3033.2024.07.0146
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doi: 10.16265/j.cnki.issn1003-3033.2024.07.0146
  • Receive Date：2024-01-15
  • Online Date：2025-07-09
  • Published：2024-07-28
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  • Received：2024-01-15
  • Revised：2024-04-18
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Affiliations
    1 School of Environment and Resources，Southwest University of Science and Technology，Mianyang Sichuan 621010，China
    2 Sichuan Institute of Safety Science and Technology，Chengdu Sichuan 610045，China
    3 Sichuan Key Laboratory of Measurement and Control of Major Hazardous Sources，Chengdu Sichuan 610045，China
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表12种不同金属材料的力学参数
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Number of
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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