This paper presents an innovative optimized modeling strategy that integrates experimental data to enhance the applicability of the traditional Gaussian plume model.The Gaussian plume model has been significantly improved through the introduction of a height correction factor,He,which is derived from an analysis of the forces acting on a unit of gas,thereby establishing the relationship between diffusion velocity and density.The height correction factor is then employed to optimize the Gaussian model for CO2 plumes,thereby improving the model's capability to simulate CO2 diffusion behavior.This optimized model was subsequently subjected to extensive comparison and validation against monitoring data from a 258-meter-long industrial-scale CO2 pipeline leakage experiment.The results demonstrate that the model significantly enhances the accuracy of reverse calculations of source strength.Further analysis indicates that,to ensure high precision in estimating source strength and leakage location,it is essential to develop customized CO2 diffusion models for the three different leakage scenarios.A comparison between the experimental results and model calculations reveals that,when predicting the volume fraction at specific monitoring points,the maximum error is maintained within 7.01％.This demonstrates that the corrected Gaussian model is suitable for risk prediction in diffusion areas.Additionally,during the reverse calculation of source strength,errors are as low as 0.94％and 0.69％.Even in instances where the error reaches 9.61％,it remains below 10％.Furthermore,the difference in the predicted coordinates of the leakage source in the reverse calculation is within 10 meters,thereby fully validating the high accuracy of this reverse prediction model.The reverse calculation method proposed in this paper,which is based on optimized modeling with experimental data,not only demonstrates high predictive accuracy but also shows potential for application in emergency response scenarios involving leaks in Carbon Capture,Utilization,and Storage(CCUS)systems.This method supports the enhancement of the overall safety and reliability of CCUS technology by facilitating safety assessments and enabling rapid predictions.
关键词
安全工程/CO2泄漏风险评估/逆向计算方法/CO2工业级试验/高斯羽流
Key words
safety engineering/CO2 leakage risk assessment/reverse calculation method/industrial-scale CO2 experiment/Gaussian plume
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