Search Results (7)

The hydration heat generated during the concreting of cast-in-place piles causes thermal disturbance to the surrounding permafrost, leading to its thawing. This further affects the stability of the pile foundation and degrades the construction progress. To explore the influence mechanisms of the concrete hydration heat on the permafrost temperature field around the pile, as well as that of different construction seasons on the pile-side boundary conditions and permafrost temperature field, monitoring results of on-site tests and numerical simulation were used to analyze the distribution law of the pile soil temperature field in space and time, and the pile-side boundary conditions and permafrost temperature field during construction seasons. The results show that the temperature trend of the pile foundation can be divided into three stages: a rapid rise phase (0∼2 d), a rapid decline phase (2∼10 d), and a slow decline and stabilization phase (10∼90 d). As the radial distance from the pile center decreases, there occur a corresponding acceleration in temperature increase and an elevated maximum temperature rise (MTR). The influence range of the molding temperature and the hydration heat is about 1∼2 times the pile diameter and less than 1.5 m in the depth direction. Compared to the atmospheric temperature, there is a lag in the change in the permafrost temperature caused by accumulation of ground temperature, and the significant difference between the two leads to an increased rate of heat exchange at the boundary condition. Conducting drilling operation and cast-in-place pile construction in the cold seasons is conducive to reducing the thermal disturbance to the permafrost around the pile in permafrost areas. Full article

In order to solve the problem of image boundary segmentation caused by the irregularity of paddy fields in southern China, a high-precision segmentation method based on the improved MultiResUNet model for paddy field mapping is proposed, combining the characteristics of paddy field scenes. We introduce the attention gate (AG) mechanism at the end of the encoder–decoder skip connections in the MultiResUNet model to generate the weights and highlight the response of the field ridge area, add an atrous spatial pyramid pooling (ASPP) module after the end of the encoder down-sampling, use an appropriate combination of expansion rates to improve the identification of small-scale edge details, use 1 × 1 convolution to improve the range of the sensory field after bilinear interpolation to increase the segmentation accuracy, and, thus, construct the AM-UNet paddy field ridge segmentation model. The experimental results show that the IoU, precision, and F1 value of the AM-UNet model are 88.74%, 93.45%, and 93.95%, respectively, and that inference time for a single image is 168ms, enabling accurate and real-time segmentation of field ridges in a complex paddy field environment. Thus, the AM-UNet model can provide technical support for the development of vision-based automatic navigation systems for agricultural machines. Full article

The underground space in the Starting Area in the Guangzhou International Financial City is being developed to save resources and improve land benefits. However, high-density development has increased the likelihood of fires. Therefore, PyroSim and Pathfinder were used in this study to investigate the fire smoke flow and personnel evacuation in the underground space in the Starting Area. Firstly, the 2D temperature cloud map and the temperature and visibility recorded by sensor A over time of Zone I in the Starting Area were analyzed. Then, the 3D smoke diffusion, the 3D temperature diffusion map, and the value of thermocouple and smoke obscuration recorded by sensors of Zone II were analyzed. Next, smoke flow of Zones III to V in the Starting Area under different fire source positions was simulated. Finally, the personnel evacuation model was established to simulate the personnel flow rate and density. The simulation results show that the available safe evacuation time for people is 530 s when all the firefighting facilities fail and fire breaks out in Zone I. For large public spaces, the overall spread speed of fire is fast, which requires the use of the fire control system in time to control the spread of fire. Fortunately, the space of evacuation time is relatively sufficient; it only takes 143 s to evacuate personnel safely in Zone II, which is sufficient compared to the time for the fire to completely spread. Suggestions were made for fire safety management, such as evacuating personnel to the safety exits of other adjacent areas during a fire and installing linkage fire alarm systems in large public space s. Full article

Inspired by the flapping wings of seagulls during flight, a new low-cost, magnet-free, bistable piezoelectric energy harvester is proposed to obtain energy from low-frequency vibration and convert it into electrical energy and reduce fatigue damage caused by stress concentration. In order to optimize the power generation efficiency of this energy harvesting, finite element analysis and experimental tests were carried out. The results of finite element analysis and experimental results are in good agreement, and the superior performance in improving stress concentration of the energy harvester compared to the previous parabolic (bow-shaped) one using bistable technology was quantitatively analyzed using finite element simulation, with a maximum stress reduction of 32.34%. The experimental results showed that under optimal operating conditions, the maximum open-circuit voltage of the harvester was 11.5 V, and the maximum output power was 73 μW. These results indicate that this is a promising strategy, which provides a reference for collecting vibrational energy in low-frequency environments. Full article

Agricultural robotics is a complex, challenging, and exciting research topic nowadays. However, orchard environments present harsh conditions for robotics operability, such as terrain irregularities, illumination, and inaccuracies in GPS signals. To overcome these challenges, reliable landmarks must be extracted from the environment. This study addresses the challenge of accurate, low-cost, and efficient landmark identification in orchards to enable robot row-following. First, deep learning, integrated with depth information, is used for real-time trunk detection and location. The in-house dataset used to train the models includes a total of 2453 manually annotated trunks. The results show that the trunk detection achieves an overall mAP of 81.6%, an inference time of 60 ms, and a location accuracy error of 9 mm at 2.8 m. Secondly, the environmental features obtained in the first step are fed into the DWA. The DWA performs reactive obstacle avoidance while attempting to reach the row-end destination. The final solution considers the limitations of the robot’s kinematics and dynamics, enabling it to maintain the row path and avoid obstacles. Simulations and field tests demonstrated that even with a certain initial deviation, the robot could automatically adjust its position and drive through the rows in the real orchard. Full article

Guava fruit is readily concealed by branches, making it difficult for picking robots to rapidly grip. For the robots to plan collision-free paths, it is crucial to segment branches and fruits. This study investigates a fast and accurate obstacle segmentation network for guava-harvesting robots. At first, to extract feature maps of different levels quickly, Mobilenetv2 is used as a backbone. Afterwards, a feature enhancement module is proposed to fuse multi-level features and recalibrate their channels. On the basis of this, a decoder module is developed, which strengthens the connection between each position in the feature maps using a self-attention network, and outputs a dense segmentation map. Experimental results show that in terms of the mean intersection over union, mean pixel accuracy, and frequency weighted intersection over union, the developed network is 1.83%, 1.60% and 0.43% higher than Mobilenetv2-deeplabv3+, and 3.77%, 2.43% and 1.70% higher than Mobilenetv2-PSPnet; our network achieved an inference speed of 45 frames per second and 35.7 billion floating-point operations per second. To sum up, this network can realize fast and accurate semantic segmentation of obstacles, and provide strong technical and theoretical support for picking robots to avoid obstacles. Full article

We have investigated tunable terahertz (THz) phase shifters that are based on a sandwiched liquid crystal (LC) cell with indium–tin–oxide (ITO) nanowhiskers (NWhs) as transparent electrodes. More than 360° of phase shift at 1.0 THz was achieved at a driving voltage as low as ~2.6 V (rms). This is approximately 40 times smaller than that reported in previous works using an electrically tuned LC device. Significance of the NWhs in reducing the required voltage is demonstrated. Overall transmittance of the device is as high as 30%, which is accountable by absorption losses of ITO NWhs, quartz substrate and LC. Experimental results are in good agreement with a theoretical formulism while taking into account super-thick LC cells (~1 mm) and pretilt angles. We also propose and demonstrate a novel THz technique for measuring pretilt angles of liquid crystals. Full article