Study on the Impact of Health Condition Registration and Temperature Check on Inbound Passenger Flow and Optimisation Measures in a Metro Station during the COVID-19 Pandemic

The Guangzhou Metro Authority implemented health condition registration and temperature checks to curb the spread of the virus during the COVID-19 pandemic. However, it is important to investigate how these measures may have impacted the get-through efficiency and whether they caused the increased crowding at entrances and the station hall. To address these questions, simulation models based on the T Station were developed using AnyLogic. The model compared the get-through efficiencies with and without the anti-epidemic measures, while also analysing the risk of crowding at entrances and within the station hall after their implementation. Results revealed an increase in the number of passengers unsuccessfully passing through the check-in gate machines from 15% to 53% within 5 minutes, and 10% to 45% within 10 minutes when the anti-epidemic measures were in place. It was also observed that some entrances experienced significant crowding. Three measures were simulated to find effective ways to increase the get-through efficiency and mitigate the crowding – increasing the distance between security and health checks, utilising automatic infrared thermometers, and arranging volunteers or staff to assist with the registration process. The results demonstrated that using automatic infrared thermometers instead of handheld forehead thermometers proved to be effective in improving passenger efficiency and alleviating crowding at entrances and within the station hall

Springback analysis of AA5754 after hot stamping: experiments and FE modelling

In this paper, the springback of the aluminium alloy AA5754 under hot stamping conditions was characterised under stretch and pure bending conditions. It was found that elevated temperature stamping was beneficial for springback reduction, particularly when using hot dies. Using cold dies, the flange springback angle decreased by 9.7 % when the blank temperature was increased from 20 to 450 °C, compared to the 44.1 % springback reduction when hot dies were used. Various other forming conditions were also tested, the results of which were used to verify finite element (FE) simulations of the processes in order to consolidate the knowledge of springback. By analysing the tangential stress distributions along the formed part in the FE models, it was found that the springback angle is a linear function of the average through-thickness stress gradient, regardless of the forming conditions used

One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer

Whole-body mesh recovery aims to estimate the 3D human body, face, and hands parameters from a single image. It is challenging to perform this task with a single network due to resolution issues, i.e., the face and hands are usually located in extremely small regions. Existing works usually detect hands and faces, enlarge their resolution to feed in a specific network to predict the parameter, and finally fuse the results. While this copy-paste pipeline can capture the fine-grained details of the face and hands, the connections between different parts cannot be easily recovered in late fusion, leading to implausible 3D rotation and unnatural pose. In this work, we propose a one-stage pipeline for expressive whole-body mesh recovery, named OSX, without separate networks for each part. Specifically, we design a Component Aware Transformer (CAT) composed of a global body encoder and a local face/hand decoder. The encoder predicts the body parameters and provides a high-quality feature map for the decoder, which performs a feature-level upsample-crop scheme to extract high-resolution part-specific features and adopt keypoint-guided deformable attention to estimate hand and face precisely. The whole pipeline is simple yet effective without any manual post-processing and naturally avoids implausible prediction. Comprehensive experiments demonstrate the effectiveness of OSX. Lastly, we build a large-scale Upper-Body dataset (UBody) with high-quality 2D and 3D whole-body annotations. It contains persons with partially visible bodies in diverse real-life scenarios to bridge the gap between the basic task and downstream applications.Comment: Accepted to CVPR2023; Top-1 on AGORA SMPLX benchmark; Project Page: https://osx-ubody.github.io

Synchronous and subsynchronous vibration under the combined effect of bearings and seals: numerical simulation and its experimental validation

A three-dimensional computational fluid dynamics (CFD) model of a labyrinth seal was established in order to investigate the influence mechanism of combined effects between bearings and labyrinth seals on the dynamic characteristics of the rotor-bearing-seal system. The dynamic coefficients of the labyrinth seal for various rotating speeds were calculated. Results show that the absolute values of cross-coupled coefficients increase with the increasing rotating speed, while the absolute values of direct coefficients decrease slightly. The positive preswirl at the inlet tends to intensify the increase of cross-coupled coefficients and the decrease of direct coefficients. The negative preswirl shows the opposite effect. A finite element model was further setup. Results show that the labyrinth seal has a large influence on the synchronous response of rotor in the resonant region due to its damping effect. For other speeds, it has a minor effect. The labyrinth seal may promote the instability of the rotor-bearing-seal system. The subsynchronous vibration increases significantly when the seal force is taken into account. The system stability can be generally enhanced by introducing the negative preswirl at the inlet. Results also show that the detrimental influence of the labyrinth seal can be compensated by using suitable bearings. A proper bearing configuration can be designed to reduce the risks of rotordynamic instabilities due to seals. An experimental test was finally performed, and it shows good agreements with the numerical simulation

The influence of phosphorus precursor on the structure and properties of SiO2-P2O5-CaO bioactive glass

Bioactive glasses (BGs) are one of the most promising bone regeneration materials because they can bond to bone and simulate new bone growth. Sol-gel methods for producing BG are well established, however challenges still remain in selecting and optimizing the precursors. Even for BGs with the same final composition, different precursors may lead to different structures and properties of the gel derived BG. In this work, three different phosphorus precursors, phytic acid (PA), triethyl phosphate (TEP) and n-butyl phosphate (BP) were used to prepareBG (54.2%SiO2-35%CaO-10.8%P2O5, mol%). The obtained materials were characterized by TGA, FTIR, XRD, HEXRD, solid state 31P, 29Si NMRand by in vitro tests in SBF. It was found that the materials prepared by TEP or BP showed small amounts of crystallization, whereas the resulting material prepared by PA remained amorphous and had more P atoms as orthophosphate. In vitro assays indicated that all these materials were bioactive, while the BG prepared by PA showed the highest in vitro bioactivity, followed by TEP and, finally, BP. Based on these observations, it appears that phosphorus precursors have a significant impact on both the structure and bioactivity of the sol-gel derived BG. Results suggest that PA should be used in preference to TEP or n-butyl phosphate for the synthesis of sol gels. PA may improve the homogeneity of the sol gel glasses, reduce crystallization and lower stabilization temperatures

Introducing Depth into Transformer-based 3D Object Detection

In this paper, we present DAT, a Depth-Aware Transformer framework designed for camera-based 3D detection. Our model is based on observing two major issues in existing methods: large depth translation errors and duplicate predictions along depth axes. To mitigate these issues, we propose two key solutions within DAT. To address the first issue, we introduce a Depth-Aware Spatial Cross-Attention (DA-SCA) module that incorporates depth information into spatial cross-attention when lifting image features to 3D space. To address the second issue, we introduce an auxiliary learning task called Depth-aware Negative Suppression loss. First, based on their reference points, we organize features as a Bird's-Eye-View (BEV) feature map. Then, we sample positive and negative features along each object ray that connects an object and a camera and train the model to distinguish between them. The proposed DA-SCA and DNS methods effectively alleviate these two problems. We show that DAT is a versatile method that enhances the performance of all three popular models, BEVFormer, DETR3D, and PETR. Our evaluation on BEVFormer demonstrates that DAT achieves a significant improvement of +2.8 NDS on nuScenes val under the same settings. Moreover, when using pre-trained VoVNet-99 as the backbone, DAT achieves strong results of 60.0 NDS and 51.5 mAP on nuScenes test. Our code will be soon.Comment: revisio