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The novel centrifugal micro hydrodynamic axial-thrust bearing has been demonstrated to substantially mitigate the wear in hydrodynamic suspension micropumps. To further elevate the bearing performance, the flow mechanism is systematically analyzed via numerical simulations and experiments in this work. The effects of various properties of bearing on the performance are explored and explained. Results indicate that the load capacity augments with the growth of inlet-suction flow rate and with the reduction of rotational speed. Meanwhile, it initially decreases and then increases as fluid film thickness expands. Further, the bearing exhibits proper stiffness and adaptable anti-abrasion when thickness maintains 0.3 mm. This study provides a profound understanding of centrifugal micro hydrodynamic axial-Thrust bearing, and identifies its optimization measures. • The mechanism of bearing involves a combination of centrifugation and inlet-suction. • The effects of various properties of bearing on the performance are explored and explained. • The parameters are identified to optimize the bearing performance. • A novel measurement rig to assess the load capacity is proposed. • This bearing structure and its mechanism can also be extended to other mechanical devices. [ABSTRACT FROM AUTHOR]

Computer vision models are currently making great strides in object detection with the rapid development of deep convolutional detectors. However, generating a large number of anchors is an indispensable step in the object detection models for locating targets, which inevitably leads to redundant detections and low computational efficiency. Detecting contours in an image is a fundamental cognitive ability in human vision system, which offers effective evidences for object detection. This paper proposes a novel and simple method by utilizing the distribution of line segments to facilitate the Non-Maximum Suppression (NMS) for the object detection models. Multiple differentiated metrics are designed for the overlap measure between bounding boxes. As a post-processing technique, the proposed segment-based NMS can be easily applied by various models. Furthermore, the proposed method is verified on multiple benchmarks and extensive experiments have been implemented to illustrate its effectiveness. [ABSTRACT FROM AUTHOR]

The performance of the gas attenuator (GAT) with argon as the working medium for the high repetition frequency free electron laser facility (SHINE) is simulated and investigated by means of the finite element numerical simulation method, and the results of the temperature and normalized density distribution of the gas inside the active gas cell at steady state are obtained, demonstrating the density depression effect of the internal gas and the corresponding attenuation results. Under the assumption of equivalent continuous-wave (CW) power input, the gas pressures are obtained for photon intensity attenuation of 103 at different photon energy (0.4–7 keV) and repetition frequencies (1 kHz, 10 kHz, 100 kHz), and compared with the theoretical calculations. The results show that the density depression is gradually enhanced with the increase in the repetition frequency, and the nonlinear deviation of the simulation attenuation gas pressure relative to the theoretical value is also gradually increased. The thermal outflux on the wall of the active gas cell gradually decreases along the beam path, so the cooling system needs extra attention to the inlet region of the cell. According to the simulation results, at the highest operating repetition frequency of 100 kHz, the attenuation gas pressure varies from 0.0767 to 17 Torr, and the highest wall thermal outflux value reaches 52.1 W/m2. The study provides a useful reference for the performance prediction and subsequent optimization design of the gas attenuator. [ABSTRACT FROM AUTHOR]

Numerical simulation of biomass gasification in fluidized bed reactors faces several challenges including proper modeling of the physical and chemical processes involved in the gasification and numerical stiffness of the two-phase dense particle flow problem. In this paper, the multi-phase particle-in-cell (MP-PIC) model coupled with a recently developed distribution kernel method (DKM) and a new one-step pyrolysis model are employed to investigate biomass gasification in two lab-scale fluidized bed gasifiers (FBGs). The results are evaluated by comparing with the results from the Particle Centroid Method (PCM) and experimental measurements. The performance of DKM is shown to improve the robustness of the model and the new pyrolysis model is shown to improve the sensitivity of the yields of gasification products to operating temperature. The simulation results using the new pyrolysis model agree well with the experimental data under different gasification conditions. The model is shown to be able to capture the trend of gas products with respect to variations of steam/biomass ratio (SR) and operating temperature (T r). The mechanisms of the formation of gas products are analyzed based on the numerical results. By increasing the SR and T r , the production of H 2 and CO 2 is shown to increase while the production of CO and CH 4 to decrease. It is shown that varying the steam/biomass ratio in the range of 0.8 ∼ 2.0 has a minor effect on the pyrolysis process and heterogeneous reactions, while homogeneous reactions are significantly affected, leading to changes in the final composition of the gas products. Varying the gasifier temperature T r has on the other hand a crucial effect on the pyrolysis process and as such a significant impact on the gasification products and carbon conversion. • An empirical one-step model was developed for biomass pyrolysis. • Prediction of gasification products at varying operating temperatures was improved. • Impact of steam/biomass ratio on gasification products was identified. • A distribution kernel model is shown to resolve local particle over-loading problem. [ABSTRACT FROM AUTHOR]