During the research and development of multiphase flowmeters, errors are often used to evaluate the advantages and disadvantages of different devices and algorithms, whilst an in-depth uncertainty analysis is seldom carried out. However, limited information is sometimes revealed from the errors, especially when the test data are scant, and this makes an in-depth comparison of different algorithms impossible. In response to this problem, three combinations of sensing methods are implemented, which are the “capacitance and cross-correlation”, the “cross-correlation and differential pressure” and the “differential pressure and capacitance” respectively. The analytical expressions of the gas/liquid flowrate and the associated standard uncertainty have been derived, and Monte Carlo simulations are carried out to determine the desired probability density function. The results obtained through these two approaches are basically the same. Thereafter, the sources of uncertainty for each combination are traced and their respective variations with flowrates are analyzed. Further, the relationship between errors and uncertainty is studied, which demonstrates that the two uncertainty analysis approaches can be a powerful tool for error prediction. Finally, a novel multi-sensor fusion algorithm based on the uncertainty analysis is proposed. This algorithm can minimize the standard uncertainty over the whole flowrate range and thus reduces the measurement error.

Although the use of a classical Venturi tube for wet gas metering has been extensively studied in the literature, the use of an extended-throat Venturi (ETV) tube has rarely been reported since its first proposal by J. R. Fincke in 1999. The structure of an ETV is very simple, but due to the complexity of multiphase flow, its theoretical model has not been fully established yet. Therefore, in this paper theoretical models have been developed for the convergent and throat sections of an ETV, and the gradients of front and rear differential pressures are derived analytically. Several flowrate algorithms have been proposed and compared with the existing ones. Among them, the iteration algorithm is found to be the best. A reasonable explanation is provided for its performance. The relationship between the differential pressure gradient and the flowrate relative error is also studied, such that the relative error distributions varying with ETV measured flowrates can be derived. The gas flowrate error of ETV increases with the liquid content whilst the liquid flowrate error of ETV decreases with the liquid content, and the relative errors of liquid flowrate are generally 2 to 3 times larger than that of the gas flowrate. Finally, the ETV tends to be more accurate than the classical Venturi tube. The ETV can be designed more compact under the same signal intensity due to its significantly higher velocity in the throat section.

The influences of sea surface wind on the oceanic mesoscale eddy are complex. By integrating our self-developed surface drifters with satellite observations, we examined the influence of sea surface wind on the distribution of water masses and biomass within the interior of an anticyclonic eddy. Ten drifters were deployed in the northern South China Sea in the spring of 2021. Eventually, six were trapped in an anticyclonic mesoscale eddy for an extended period. Interestingly, the drifters’ trajectories were not symmetric around the eddy center, displaying a significant offset of the distance from the wind turns to the southerly wind. Particle tracking experiments demonstrated that this departure could mainly be attributed to wind-driven ageostrophic currents. This is due to the strength of wind-driven ageostrophic currents being more comparable to geostrophic currents when accompanied by a deflection between the directions of the wind-driven current and the eddy’s translation. The drifters’ derived data indicated that sub-mesoscale ageostrophic currents within the eddy contributed to this asymmetric trajectory, with Ekman and non-Ekman components playing a role. Furthermore, the evolution of ocean color data provided corroborating evidence of these dynamic processes, highlighting the importance of ageostrophic processes within mesoscale eddies.

Wind farms, as an important renewable energy source to combat climate change, have had explosive development in recent years. Assessing impacts of wind farms on atmospheric and marine environments requires an accurate parameterization of wind farms in atmospheric models. The current wind farm parameterization scheme (Fitch et al. 2012) in WRF plays an important role in the study of impacts of wind farms. The scheme, however, has some shortfalls, e.g., does not consider the wind wake behind turbines inside a grid cell. In this research, the Fitch scheme in WRF is modified by inclusion of the wake effect of wind turbines. Based on an engineering wake model of a turbine, a wake superposition coefficient and an angle correction coefficient are proposed. A solution model for the inflow wind speed is established to obtain the angle correction coefficient. Other coefficients in the engineering wake model are calculated based on the CFD results. These coefficients are added in the WRF to improve the wind farm parameterization, and sensitivity experiments are conducted. Model results show that the new improved scheme significantly increases wind energy, output power and turbulent kinetic energy in the wind farm area compared with the original scheme. Sensitivity experiments also reveal that, with enlarged model grid size and shortened turbine spacing, the subgrid wake effect becomes more significant, and the new scheme shows more advantages.