Prediction of gas leakage and dispersion in utility tunnels based on CFD-EnKF coupling model: A 3D full-scale application

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 threedimensional 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.

Automated summary

This study proposes a three-dimensional source term estimation (3D-STE) model using computational fluid dynamics (CFD) and ensemble Kalman filter (EnKF) algorithm to predict gas concentration and estimate gas leakage sources. The model is validated through a twin experiment, showing its effectiveness and practicality.