Effect of calcium aluminate cement variety on the hydration of Portland cement in blended system

Two kinds of CACs with different monocalcium aluminate (CA) contents were used in the PC/CAC (PAC) mixtures. Effects of CA and CACs on the properties of PAC were analyzed by setting times and the compressive strength tests, and also by means of calorimetry, XRD, DTA-TG and ESEM. The experimental results show that the compressive strength of the PAC mortars decreases with increasing content of CAC while it declines sharply with a higher content of CA in CAC. Compared with neat PC paste, the content of calcium hydroxide in hydrates of PAC paste decreases significantly, and the hydration time of PC is prominently prolonged. Additionally, the higher the content of CA in CAC, the more obviously the hydration of PC is delayed, confirming that the CA phase in CAC plays an important role in the delay of PC hydration

Effect of magnetostatic field on microstructure of 5005 aluminum alloy sheet by roll-casting

The roll-casting technology of 5000 series aluminum alloy is one of the difficulties at present. Roll-casting technology was employed in this paper and high quality 5005 aluminum alloy sheets were fabricated successfully under different conditions. The solidification of melt in roll-casting process is the rapid directional solidification. The effect of magnetostatic field on microstructure of 5005 aluminum alloy sheet by roll-casting has been investigated and analyzed. The results indicate that imposing magnetostatic field can refine the grains of 5005 aluminum alloy

SeqOT: A Spatial-Temporal Transformer Network for Place Recognition Using Sequential LiDAR Data

Place recognition is an important component for autonomous vehicles to achieve loop closing or global localization. In this paper, we tackle the problem of place recognition based on sequential 3D LiDAR scans obtained by an onboard LiDAR sensor. We propose a transformer-based network named SeqOT to exploit the temporal and spatial information provided by sequential range images generated from the LiDAR data. It uses multi-scale transformers to generate a global descriptor for each sequence of LiDAR range images in an end-to-end fashion. During online operation, our SeqOT finds similar places by matching such descriptors between the current query sequence and those stored in the map. We evaluate our approach on four datasets collected with different types of LiDAR sensors in different environments. The experimental results show that our method outperforms the state-of-the-art LiDAR-based place recognition methods and generalizes well across different environments. Furthermore, our method operates online faster than the frame rate of the sensor. The implementation of our method is released as open source at: https://github.com/BIT-MJY/SeqOT.Comment: Submitted to IEEE Transactions on Industrial Electronic