Study on the Behaviors of a Conceptual Passive Containment Cooling System

The containment is an ultimate and important barrier to mitigate the consequences after the release of mass and energy during such scenarios as loss of coolant accident (LOCA) or main steam line break (MSLB). In this investigation, a passive containment cooling system (PCCS) concept is proposed for a large dry concrete containment. The system is composed of series of heat exchangers, long connecting pipes with relatively large diameter, valves, and a water tank, which is located at the top of the system and serves as the final heat sink. The performance of the system is numerically studied in detail under different conditions. In addition, the influences of condensation heat transfer conditions and containment environment temperature conditions are also studied on the behaviors of the system. The results reveal that four distinct operating stages could be experienced as follows: startup stage, single phase quasisteady stage, flashing speed-up transient stage, and flashing dominated quasisteady operating stage. Furthermore, the mechanisms of system behaviors are thus analyzed. Moreover, the feasibility of the system is also discussed to meet the design purpose for the containment integrity requirement. Considering the passive feature and the compactness of the system, the proposed PCCS is promising for the advanced integral type reactor

Dynamic experimental investigation on the volatilization behavior of lead and cadmium in the simulated Municipal Solid Waste (MSW) influenced by sulfur compounds during incineration

In China, coal, often with a high level of sulfur, is always mixed with municipal solid waste (MSW) in waste incineration plants due to the low heating value and high moisture content of MSW. The influence of sulfur compounds on the volatilization of heavy metals in MSW is of great concern for China’s waste incineration plants. In this study, the continuous dynamic volatilization process of Pb and Cd is investigated by adding different forms of sulfur compounds, elemental sulfur (S), and sodium sulfate (Na2SO4), to the simulated MSW in a laboratory incinerator, at both 1 and 3 wt %, respectively. The experimental results show that the added S begins to affect the volatilization of Pb and Cd at about 700 °C; adding S can lead up to 49.6% reduction in the volatilization of Pb, as the produced sulfur dioxide is promoting the formation of a condensed sulfate phase, and part of Pb is fixed in the form of PbS in the bottom ash. But for Cd, adding S causes up to 15.9% increase in its volatilization as S seizes part of O2 in the air, which is conducive to forming the reducing atmosphere. In the reducing atmosphere, CdO can be easily reduced to Cd, which volatilizes more easily than CdO at high temperatures. In fact, in the reducing atmosphere, the volatilization of Cd far outweighs the volatilization of Pb at 700–800 °C. On the other hand, adding Na2SO4 almost has no influence on the volatilization of lead and cadmium below 900 °C

Gains to Chinese Bidder Firms::Domestic vs. Foreign Acquisitions

This paper examines whether foreign acquisition of Chinese firms improves share price performance relative to domestic acquisitions. The results show that foreign acquisitions are not associated with positive abnormal returns in the short-run, but that they are so associated for domestic acquisitions. Foreign acquisitions also realise significant long-run gains, especially when the acquiring firm is large. Specifically, we find that there is a significant, positive long-run outperformance of 29.81% for large foreign acquisitions benchmarked against domestic ones, while large foreign acquisitions earn 22.39% in aggregate. Our evidence suggests that large Chinese acquirers gain when they expand their operations abroad, consistent with the literature on reverse internalisation

Deformation Detection of Mining Tunnel Based on Automatic Target Recognition

Mining tunnels have irregular and diverse cross-sectional shapes. Structural deformation detection using mobile laser measurement has some problems, such as the inconvenient positioning of the deformation, difficulties in unifying the multiphase data, and difficulties in solving the section parameters. To address these problems, this paper proposes a mining tunnel deformation detection method based on automatic target recognition. Firstly, a mobile tunnel laser detection scheme combined with the target layout is designed. Secondly, a preview image of the tunnel lining is generated using the mobile laser point cloud data, and the index relationship between the image and point cloud is established. The target recognition accuracy of the You Only Look Once version 4 (YOLOv4) model is optimized by integrating the prediction confidence threshold, target spatial position, and target gray scale rule. Based on target recognition and positioning, the chord length and vault net height of the mining tunnel are calculated using gross error elimination and curve fitting. Finally, the engineering application of the model and algorithm is realized using ML.NET. The research method was verified using the field measurement data of the mining tunnel. The target recognition accuracy reached 100%, and the repeated deviations of the chord length and net height of the arch crown were 1.7 mm and 1.4 mm, respectively, which established the effectiveness and high accuracy of the research method

Precise Positioning Method of Moving Laser Point Cloud in Shield Tunnel Based on Bolt Hole Extraction

Mobile laser scanning technology used for deformation detection of shield tunnel is usually two-dimensional, which is expanded into three-dimensional (3D) through mileage, resulting in low positioning accuracy. This study proposes a 3D laser point cloud positioning method that is divided into rings in the mileage direction and blocks in the ring direction to improve the positional accuracy for shield tunnels. First, the cylindrical tunnel wall is expanded into a plane and the bolt holes are extracted using the self-adaptive parameter adjustment cloth simulation filter (CSF) algorithm combined with a density-based spatial clustering of applications with noise (DBSCAN) algorithm. Second, the mean-shift algorithm is used to obtain the center point of the bolt hole, and a model is designed to recognize the center point of different splicing blocks. Finally, the center point is combined with the standard straight-line equation to fit the straight-line positioning seam, achieving an accurate ring and block segmentation of a shield tunnel as a 3D laser point cloud. The proposed method is compared with existing methods to verify its feasibility and high accuracy using the seams located by the measured tunnel point cloud data and in the measured point cloud. The average differences between the circumferential seams positioned using the proposed method and those in the point cloud at the left waist, vault, and right waist were 3, 4, and 5 mm, respectively, and the average difference between the longitudinal seams was 3.4 mm The proposed research method provides important technical and theoretical support for tunnel safety monitoring and detection

Precise Positioning Method of Moving Laser Point Cloud in Shield Tunnel Based on Bolt Hole Extraction

Mobile laser scanning technology used for deformation detection of shield tunnel is usually two-dimensional, which is expanded into three-dimensional (3D) through mileage, resulting in low positioning accuracy. This study proposes a 3D laser point cloud positioning method that is divided into rings in the mileage direction and blocks in the ring direction to improve the positional accuracy for shield tunnels. First, the cylindrical tunnel wall is expanded into a plane and the bolt holes are extracted using the self-adaptive parameter adjustment cloth simulation filter (CSF) algorithm combined with a density-based spatial clustering of applications with noise (DBSCAN) algorithm. Second, the mean-shift algorithm is used to obtain the center point of the bolt hole, and a model is designed to recognize the center point of different splicing blocks. Finally, the center point is combined with the standard straight-line equation to fit the straight-line positioning seam, achieving an accurate ring and block segmentation of a shield tunnel as a 3D laser point cloud. The proposed method is compared with existing methods to verify its feasibility and high accuracy using the seams located by the measured tunnel point cloud data and in the measured point cloud. The average differences between the circumferential seams positioned using the proposed method and those in the point cloud at the left waist, vault, and right waist were 3, 4, and 5 mm, respectively, and the average difference between the longitudinal seams was 3.4 mm The proposed research method provides important technical and theoretical support for tunnel safety monitoring and detection

Enhanced Water Leakage Detection in Shield Tunnels Based on Laser Scanning Intensity Images Using RDES-Net

Tunnel water leakage detection is the difficulty and bottleneck in shield tunnel operation monitoring. This article introduces the RDES method for detecting water leakage in shield tunnels. First, to enhance the model's information extraction capabilities, we introduce a detection-efficient efficient 3 normalized conv1ds of attention module by combining the characteristics of the attention mechanisms, efficient channel attention, and coordinate attention. This module aims to focus the model's backbone network on capturing the spatial features of water leakage data and facilitating meaningful interaction between different channels. In addition, we design the residual deformable convolution to provide the convolutional energy with the flexibility to detect deformed targets, thereby enhancing the model's recognition ability. Finally, we incorporate a nonmaximum suppression technique during prediction to improve detection accuracy. This technique retains more bounding boxes by applying soft-NMS weighted averaging. The results of the measured and publicly available data show that the RDES algorithm outperforms all the compared algorithms and is advanced and efficient. The results show that compared with the baseline, the RDES algorithm improves the F1 metrics, mAP0.5, mAP0.75, and mAP by 2.2%, 4.4%, 9.2%, and 5.2% on the laser intensity image dataset, and by 3.1%, 4.6%, 7.9%, and 5.9% on the optical image dataset

3D Point Cloud Generation Based on Multi-Sensor Fusion

Traditional precise engineering surveys adopt manual static, discrete observation, which cannot meet the dynamic, continuous, high-precision and holographic fine measurements required for large-scale infrastructure construction, operation and maintenance, where mobile laser scanning technology is becoming popular. However, in environments without GNSS signals, it is difficult to use mobile laser scanning technology to obtain 3D data. We fused a scanner with an inertial navigation system, odometer and inclinometer to establish and track mobile laser measurement systems. The control point constraints and Rauch-Tung-Striebel filter smoothing were fused, and a 3D point cloud generation method based on multi-sensor fusion was proposed. We verified the method based on the experimental data; the average deviation of positioning errors in the horizontal and elevation directions were 0.04 m and 0.037 m, respectively. Compared with the stop-and-go mode of the Amberg GRP series trolley, this method greatly improved scanning efficiency; compared with the method of generating a point cloud in an absolute coordinate system based on tunnel design data conversion, this method improved data accuracy. It effectively avoided the deformation of the tunnel, the sharp increase of errors and more accurately and quickly processed the tunnel point cloud data. This method provided better data support for subsequent tunnel analysis such as 3D display, as-built surveying and disease system management of rail transit tunnels