Adaptive center constraint for joint release rate estimation and model correction: Multi-scenario validation against wind tunnel experiments

Abstract

Release rate estimation is crucial for the consequence assessment and emergency decision-making in nuclear accidents. However, inevitable model biases can lead to significant deviations. This study proposes an Adaptive Center Constraint for joint release rate estimation and model correction (ACC joint) for improved robustness and accuracy. It uses a tailored cost function to determine the optimal center constraint, which can automatically adapt to different cases. It was validated against four wind tunnel experiments, which simulated complex dispersion scenarios with densely built-up and highly heterogeneous terrains. The ACC joint method was compared with the Tikhonov and joint correction. The results indicate that the proposed method significantly improves the accuracy of release rate estimation. Compared to the joint correction method, the mean relative error is reduced by 38.6% and 31.4% in the all-measurement and independent validation, respectively. Furthermore, sensitivity analysis reveals that the ACC joint method provides lower mean relative error with different numbers of measurements and shows ultimate stability in all scenarios. It also suggests that measurement sites should be positioned in downwind high-concentration areas and the foot of mountainous areas for reliable estimation. The results from different cost functions verify the scalability of the proposed method, providing potential applications to other complex scenarios.