Diversion tunnels are often used as tailrace tunnels in underground hydropower stations. The special layout results in complex flow regimes, including air-water two-phase flow. A set of experiments is conducted based on the model of a hydropower station which combines partial diversion tunnels with tailrace tunnels to investigate the interactions between the air and water phases in the combined diversion tunnels. Interactions between the air and water phases observed in the combined diversion tunnel significantly alter flow dynamics, and are classified into four types according to the initial tail water level. There is a range of initial tail water levels in which the interaction between the air and water phases cannot be neglected, and the range becomes greater when the change in flow rate increases. Such interactions may cause a pressure surge and the pressure surge reaches the maximum when the initial tail water level is approximately equal to the crown of the tunnel. The surge pressures do harm to the safety and stability of hydropower stations, so the condition should be considered and controlled.

For some special tailrace tunnels in the hydropower stations, including the changing top-altitude tailrace tunnel and the tailrace tunnel with downstream reused flat-ceiling diversion tunnel, during normal operation and hydraulic transients, the flow patterns inside are relatively complex mainly including the free-surface pressurized flow and partial free flow if the tail water level is lower than the top elevation of tunnel’s outlet. These complex flow patterns have obvious effect on system’s stability, and can not be simulated accurately by the traditional models. Therefore, a characteristic implicit model is introduced to simulate these complex flow patterns for further stability analysis. In some special cases, the characteristic implicit model also fails to completely simulate the mixed free-surface pressurized flow in the flat-ceiling tailrace tunnel. A new method is presented based on both experimental research and numerical simulation, and then, system’s stability is analyzed by compared with traditional ordinary boundary condition. The results indicate that, with different simulation models for the complex water flow in the tailrace tunnel, system’s dynamic characteristic can be actually revealed with the consideration of the effect of complex flow patterns in the tailrace tunnel on system’s stability and regulation performance.

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This paper is the first attempt to propose an efficient auction mechanism for the regional logistics synchronization (RLS) problem, which aims to capture both logistics punctuality and simultaneity in a regional logistics network. The main motivation of RLS is motivated by our industrial collaborator, i.e. a third-party logistics (3PL) company, that if the delay has already occurred or will occur, the customers tend to pursue the simultaneity. We develop the one-sided Vickrey-Clarke-Groves (O-VCG) auction to realize incentive compatibility (on the buy side), budget balance, and individual rationality. The vehicle routing problem faced by the 3PL company is formulated as the lane covering problem with RLS requirements. Given the complexity of the proposed model, three canonical swarm intelligence meta-heuristics are employed to address the auction-based RLS problem. Besides, a superior tracking artificial bee colony with novel information learning mechanism is further developed to explore better solutions. Comparison results reveal the effectiveness of the proposed optimizers in terms of realized social welfare. Experimental results show that the O-VCG auction can achieve high synchronization level, approximately allocative efficiency and (ex post) budget balance.