Natural gas compartment accommodated in utility tunnels is beneficial in meeting the pressing demand of energy supply and sustainable urban environment. However, the leaking gas characterized by flammable and explosive can pose a huge threat to the safe operation of the utility tunnel. When an unexpected gas leakage accident happens in the actual situation, the prior information associated with the leakage source is commonly unclear or unknown. Therefore, the absence of an available tool for reasonable leakage and dispersion prediction in the above scenario precludes the timely and appropriate emergency response treatment. In this study, a three-dimensional source term estimation (3D-STE) model with the combination of the computational fluid dynamics (CFD) and ensemble Kalman filter (EnKF) algorithm is proposed to achieve spatiotemporal gas concentration prediction and gas emission source estimation. In the proposed approach, the observation data can be incorporated into the gas dispersion simulations continuously, thus the simulation results can be revised by the observation data and the source term estimation of gas leakage can be achieved by employing the EnKF algorithm. A twin experiment is employed to validate the effectiveness and practicability of the proposed model. The results show that the proposed model can revise the prior errors in the gas leakage rate significantly and obtain an accurate prediction of gas concentration distribution as well as gas leakage rate. A feasible framework is also proposed serving as a good paradigm for the 3D-STE model application. This study helps for consequence assessment and emergency response of gas leakage accidents in utility tunnels.@en

As a kind of clean fuel, increasing quantities of natural gas have been transported as liquefied natural gas (LNG) worldwide. The safety of LNG storage has gained the concerns from the public due to the potential severe consequences that may arise from LNG leakage. In this paper, a three-dimensional model with the combination of computational fluid dynamics (CFD) and the ensemble Kalman filter (EnKF) is proposed to predict LNG vapor dispersion and estimate the strength of the LNG leakage source. The LNG vapor dispersion CFD model is validated by the experimental data with good feasibility, and is further demonstrated with the reasonable modeling of the characteristics of the LNG vapor dispersion in a typical receiving terminal. The effectiveness of the proposed CFD and EnKF coupling model is evaluated and validated by a twin experiment. The results of the twin experiment indicate that the proposed CFD and EnKF coupling model allows the integration of observation data into the CFD simulations to enhance the prediction accuracy of the LNG vapor spatial-temporal distribution and thereby realizing a reasonable estimation of the LNG leakage velocity under complex environments. This study can provide technical supports for safety control, loss prevention and emergency response in case of LNG leakage accidents.

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