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The precast concrete slab track (PST) has advantages of fewer maintenance frequencies, better smooth rides and structural stability, which has been widely applied in urban rail transit. Precise positioning of precast concrete slab (PCS) is vital for keeping the initial track regularity. However, the cast-in-place process of the self-compacting concrete (SCC) filling layer generally causes a large deformation of PCS due to the water-hammer effect of flowing SCC, even cracking of PCS. Currently, the buoyancy characteristic and influencing factors of PCS during the SCC casting process have not been thoroughly studied in urban rail transit.

In this work, a Computational Fluid Dynamics (CFD) model is established to calculate the buoyancy of PCS caused by the flowing SCC. The main influencing factors, including the inlet speed and flowability of SCC, have been analyzed and discussed. A new structural optimization scheme has been proposed for PST to reduce the buoyancy caused by the flowing SCC.

The simulation and field test results showed that the buoyancy and deformation of PCS decreased obviously after adopting the new scheme.

The findings of this study can provide guidance for the control of the deformation of PCS during the SCC construction process.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.

A quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.

The proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.

CFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.

The purpose of this paper is to relate to the real-time navigation and tracking of pedestrians in a closed environment. To restrain accumulated error of low-cost microelectromechanical system inertial navigation system and adapt to the real-time navigation of pedestrians at different speeds, the authors proposed an improved inertial navigation system (INS)/pedestrian dead reckoning (PDR)/ultra wideband (UWB) integrated positioning method for indoor foot-mounted pedestrians.

This paper proposes a self-adaptive integrated positioning algorithm that can recognize multi-gait and realize a high accurate pedestrian multi-gait indoor positioning. First, the corresponding gait method is used to detect different gaits of pedestrians at different velocities; second, the INS/PDR/UWB integrated system is used to get the positioning information. Thus, the INS/UWB integrated system is used when the pedestrian moves at normal speed; the PDR/UWB integrated system is used when the pedestrian moves at rapid speed. Finally, the adaptive Kalman filter correction method is adopted to modify system errors and improve the positioning performance of integrated system.

The algorithm presented in this paper improves performance of indoor pedestrian integrated positioning system from three aspects: in the view of different pedestrian gaits at different speeds, the zero velocity detection and stride frequency detection are adopted on the integrated positioning system. Further, the accuracy of inertial positioning systems can be improved; the attitude fusion filter is used to obtain the optimal quaternion and improve the accuracy of INS positioning system and PDR positioning system; because of the errors of adaptive integrated positioning system, the adaptive filter is proposed to correct errors and improve integrated positioning accuracy and stability. The adaptive filtering algorithm can effectively restrain the divergence problem caused by outliers. Compared to the KF algorithm, AKF algorithm can better improve the fault tolerance and precision of integrated positioning system.

The INS/PDR/UWB integrated system is built to track pedestrian position and attitude. Finally, an adaptive Kalman filter is used to improve the accuracy and stability of integrated positioning system.