modelling of twin-screw pumps based on computational fluid dynamics. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, doi: 10.1177/0954406216670684 This is the accepted version of the paper.This version of the publication may differ from the final published version.
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AbstractIncreasing demands for high-performance screw pumps in oil and gas as well as other applications require deep understanding of the fluid flow field inside the machine. Important effects on the performance such as dynamic losses, influence of the leakage gaps, presence and extent of cavitation are difficult to observe by experiments. However, it is possible to study such effects using well validated CFD (computational fluid dynamics) models. The novel structured numerical mesh consisting of a single computational domain for moving screw pump rotors was developed to allow 3-D CFD simulation of such machine possible. Based on Finite Volume Method (FVM), the instantaneous mass flow rates, rotor torque, local pressure field, velocity field and other performance indicators including the indicated power were predicted. A calculation model for the bearing friction losses was introduced to account for mechanical losses. The geometry of the inlet and outlet passages and piping system are taken into consideration to evaluate their influences on the pressure distribution and shaft power. The paper also shows the influence of rotor clearances on the pump performance. The CFD model was validated by comparing the numerical results with the measured performance obtained in the experimental test rig through the comprehensive experiment performed for a set of discharge pressures and rotational speeds. Validation includes comparison of mass flow rates, shaft power and efficiency under variety of speeds and discharge pressure. It has been found that the predicted results match well with the measurements. The results also showed that that the radial clearances have larger influence on the mass flow rate than the interlobe clearance. The correct design of the flow passages within the screw pump plays significant role in minimizing required power consumption. The analysis presented in this paper contributes to better understanding of the working process inside the screw pump and offers a good reference to improve design and optimise such machines in terms of clearance selection, shape of the ports, piping system etc. In future this model will be used for analysis of cavitating flows and determining performance of other multiphase screw pumps.
Car-following is an essential trajectory control strategy for the autonomous vehicle, which not only improves traffic efficiency, but also reduces fuel consumption and emissions. However, the prediction of lane change intentions in adjacent lanes is problematic, and will significantly affect the car-following control of the autonomous vehicle, especially when the vehicle changing lanes is only a connected unintelligent vehicle without expensive and accurate sensors. Autonomous vehicles suffer from adjacent vehicles’ abrupt lane changes, which may reduce ride comfort and increase energy consumption, and even lead to a collision. A machine learning-based lane change intention prediction and real time autonomous vehicle controller is proposed to respond to this problem. First, an interval-based support vector machine is designed to predict the vehicles’ lane change intention utilizing limited low-level vehicle status through vehicle-to-vehicle communication. Then, a conditional artificial potential field method is used to design the car-following controller by incorporating the lane-change intentions of the vehicle. Experimental results reveal that the proposed method can estimate a vehicle’s lane change intention more accurately. The autonomous vehicle avoids collisions with a lane-changing connected unintelligent vehicle with reliable safety and favorable dynamic performance.
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