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百年期刊
ISSN 1000-0585
CN 11-1848/P
Started in 1982
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, Volume 63 Issue 7
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Focusing on technology innovation in intelligent inspection, building safety guarantees for hydropower hubs
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1013-1013.
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Key technology of underwater inspection robot system for large diameter and long headrace tunnel
CHEN Yongcan, CHEN Jiajie, WANG Haoran, GONG Yu, FENG Yue, LIU Zhaowei, QI Ningchun, LIU Mei, LI Yonglong, XIE Hui
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1015-1031. DOI: 10.16511/j.cnki.qhdxxb.2023.26.015
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[Significance] Headrace tunnels are key structures of major projects characterized by long tunnel lines, large tunnel diameters, high water pressure, and complex surrounding rock geology. Typical defects, such as cracks, landslides, and exposed reinforcement, will occur during long years of operation. If they are not prevented, the safe operation of the project will be seriously affected. Long cycles, high safety risk, high leak rate, and insufficient information are all issues with traditional manual inspection. Given the urgent need for regular inspection of large-diameter and super-long headrace tunnels in super-large water conservancy and hydropower projects, this study solved key scientific issues, such as the adaptability of robot underwater environment tasks, the active detection of super-long headrace tunnel apparent defects, and the safety risk assessment of tunnel structures based on robot inspection data. The key technology breakthroughs include the sub-parent cooperation of complex underwater environments, the fine operation of load manipulator, ultra-long distance underwater high-voltage power supply, umbilical cable safe release and recovery, ultra-long distance human-machine cooperative control, special environment adaptation of underwater robots, active defect detection and identification based on multi-sensor fusion. Structural safety classification, risk analysis and evaluation, and virtual drills were also carried out. The developed underwater robot inspection system was successfully applied to large-diameter and long headrace tunnels for comprehensive verification. [Progress] The application performance of underwater robots in special environments has improved due to breakthroughs in key technologies such as remote power supply, cooperative operation, intelligent patrol inspection, defect identification, and safety assessment of robots in complex underwater environments including water turbidity, high water pressure, adhesion and siltation, and local accessibility difficulties. The safety classification and risk assessment of the headrace tunnel structure are completed through the research and development of the multi-function “sub-parent” underwater robot system, and the whole process integration of “inspection, inspection, control, diagnosis, and use” of the underwater robot is realized, which has been demonstrated and verified in the eastern route of the South-to-North Water Transfer Project, Jinping Ⅱ Hydropower Station, and other major national projects, to improve the intelligent degree of the inspection of the headrace tunnel of large water conservancy and hydropower projects and support the safe operation of large projects. [Conclusions and Prospects] The research findings can significantly improve the accuracy of the headrace tunnel inspection, reduce the headrace tunnel inspection cost, and improve the guaranteed rate of the safe operation of large water conservancy and hydropower projects; promote the interdisciplinary integration of artificial intelligence and water conservancy disciplines to form interdisciplinary advantages; promote the application of robots in special environments, especially in the inspection of headrace tunnels, and guide the development of robots in special environments; promoting the application of artificial intelligence and intelligent management of water conservancy projects, as well as improving the level of technology and equipment in relevant fields in China and cultivating a large number of versatile talents, will have significant social, economic and scientific values.
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Research progress on remotely operated vehicle technology for underwater inspection of large hydropower dams
XU Pengfei, CHEN Meiya, KAI Yan, WANG Zipeng, LI Xinyu, WAN Gang, WANG Yanjie
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1032-1040. DOI: 10.16511/j.cnki.qhdxxb.2023.26.018
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[Significance] China uses a large amount of hydropower, and the safety of hydropower dams is related to the safety of people's lives, properties, and the national economy. Therefore, regular inspection of dam defects in large hydropower plants is vital to ensure their safe operation. Most of the common dam defects, such as cracks and leakage, originate from the surface of the structure and can affect the service life of the dams. In recent years, remotely operated vehicles (ROVs) have been used for the underwater inspection of dam defects in hydropower plants, as they can mitigate many disadvantages associated with manual inspections while improving detection accuracy and efficiency. [Progress] Thus, we explore the environmental conditions of dams and the main content of dam defect inspection in hydropower plants and review the research on ROV application for underwater inspection in large hydropower dams. We find that different sensors can be combined with ROVs to inspect large hydropower dams underwater according to detection and operation needs. The method can achieve intelligent mobile inspection and remote control of dam operation safety, automatically identify dam defect characteristics, and store shore-station interactive information. At present, ROVs are less used for inspecting dam defects in large hydropower plants but are widely used in fields such as deep-sea exploration, undersea operations, and rescue assistance. The use of ROVs for crack and leakage inspection in hydropower plants has tremendous advantages. The research on using ROVs for the intelligent inspection of other structures has certain implications for developing ROVs for the intelligent underwater inspection of large hydropower dams. We analyze the progress of ROV technology in domestic and international research on hydropower engineering in terms of the overall technology, underwater absorber, power system, inspection technology, underwater positioning, and control system. Moreover, we explore the modular design and overall scale optimization of ROVs for underwater inspection in large hydropower dams, with the design objectives of lightweight, high stability, and high anti-current and anti-disturbance capability. Thrusters with high propulsion ratios have been developed to ensure high ROV power. Adsorbers have been added to the ROV systems to control the hovering of ROVs, which can also improve their underwater anti-disturbance ability to ensure stable detection and operation. Acoustic-optical inspection technology has been proposed to improve detection accuracy, and intelligent algorithms have been used for defect identification and image post-processing. Regarding underwater positioning and control systems, a complementary approach combining information from multiple sensors has been adopted, and the dam defect inspection is validated to improve the operational capability of the ROV movement and inspection. [Conclusions and Prospects] The use of ROVs for underwater inspection in large hydropower dams has major advantages in targeting cracks and other dam defects, and the research on the intelligent inspection of hydropower dams opens up a wide range of prospects.
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Dynamic Bayesian network model for the safety risk evaluation of a diversion tunnel structure
LIU Kang, LIU Zhaowei, CHEN Yongcan, MA Fangping, WANG Haoran, HUANG Huibao, XIE Hui
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1041-1049. DOI: 10.16511/j.cnki.qhdxxb.2023.26.026
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[Objective] A diversion tunnel is an important part of a water conservancy project. Many factors influence the safety of a diversion tunnel structure, and the risk situation of these factors changes with time during the operating period. Analysis and evaluation of the safety of a diversion tunnel structure are important for ensuring its normal operation. However, the influence factors are complex, and the detection and evaluation of structural safety remain challenging. [Methods] In this paper, a dynamic Bayesian network model for the safety evaluation of a diversion tunnel structure was established. First, a three-level influencing index system of tunnel structure safety was determined through literature research and expert consultation, combined with the world's current tunnel safety standards. The index system included 7 aspects and 26 specific indices, such as crack length, crack width, and pH value. The risk situation of each index was divided into five levels (from A to E), with each level corresponding to a specific risk probability and risk value, aiming to quantify the risk of the diversion tunnel structure. Second, index weights were assigned through expert consultation, and the conditional probability was determined based on the fuzzy analytic hierarchy process. Finally, the prior probability was obtained through the inspection results of intelligent robots, and the transfer probability was determined according to the exponential distribution hypothesis of tunnel life. The time slice interval was set as 1 year, and the safety situation and future development trend of the diversion tunnel structural risk were calculated. In addition, by setting the overall risk level of the tunnel structure, the most likely risk probability distribution of each index was obtained through backpropagation. [Results] The model was applied to the structural safety evaluation of the diversion tunnel of a hydropower station in China, and the assessment results showed that: (1) According to forward inference, the overall risk value of the diversion tunnel was 0.230, which was very low, but lining cracks and lining spalling were structural safety problems that need attention. The evaluation results of the model were consistent with the engineering judgment. (2) The prediction of the development trend of structural risk indicated that this risk increased to 0.800 after approximately 40 years, requiring remedial action. (3) The backpropagation of risk revealed that different safety indices should receive attention in different safety periods of diversion tunnel operation. The risk influencing the degree of the lining spalling and operating environment risk was higher when the diversion tunnel was in a relatively safe state, but when the diversion tunnel was in a relatively dangerous state, the lining deformation, lining crack, and material deterioration were the main risk factors. [Conclusions] The proposed dynamic Bayesian network model performs with good accuracy and practicability for the risk assessment of a diversion tunnel structure. Furthermore, the model can predict the development trend of the structural risk and identify the key influencing index, which is important for diversion tunnel operation and maintenance.
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Temperature gradient monitoring and thermal evolution of a super mass concrete structure
AN Ruinan, LIN Peng, CHEN Daoxiang, AN Bang, LU Guannan, LIN Zhitao
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1050-1059. DOI: 10.16511/j.cnki.qhdxxb.2023.26.010
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[Objective] Bridge anchorage core concrete, a typical mass-filling marine concrete structure, faces challenges in temperature change control and crack prevention due to its special shape, continuous casting, and complicated boundary. [Methods] Based on the mass-filling concrete of the Guangxi Longmen Bridge anchorage basement (58 606 m
3
), this paper conducts an online monitoring and analysis of the real thermal field and stress distribution according to the evolution mechanism of the concrete temperature gradient during the pouring period. This work includes developing a temperature gradient digital monitoring system to provide feedback on the deviation from the actual value and provide a basis for timely warning and dynamically adjusted accurate temperature control, proposing the cracking control gradient index as the space and time gradient indices (a dimensionless index), and reconstructing the temperature field to the evolution of the real thermal field base on the temperature measurements in concrete, which is of great importance for the cracking control of the concrete structure. [Results] The main study results are as followed: (1) A major challenge in concrete cracking control was investigated according to complex structural properties, the continuous casting method, high temperature, high humidity, strong wind, and a high salt mist environment. (2) The monitoring data of the temperature gradient digital monitoring system indicated a certain difference in the temperature development in the center concrete and the area near the surface. The temperature in the concrete central area underwent a rapid increase and tended to be stable, stabilised temperature range of 53.60—54.50 ℃, and the temperature increase reached 88.16%—99.34% of the adiabatic temperature increase. The temperature near the concrete surface underwent a rapid increase and a slight decrease, peaking at 52.90 ℃. (3) The threshold values of the space gradient and time gradient indices were defined as -3.00—3.00 ℃/m and 0.002 h
-1
·m
-1
, respectively. The temperature gradient index met the threshold requirement, the horizontal and vertical spatial temperature gradients at the stable stage were -0.15—0.14 ℃/m and 0.29—1.08 ℃/m, respectively, and the time-temperature gradient was within 0.002 h
-1
·m
-1
. These results indicated that the concrete heat exchange process was performed as small temperature changes in time and space. (4) The temperature field reconstructed from the monitoring data revealed that the real temperature gradient characteristic of the mass-filling concrete and isotherms was dense near the pile foundation at 96 h, then gradually became sparse, and the time-temperature and space gradients gradually became uniform and remained uniform after 144 h. (5) The evolution of the real thermal field, from a nonuniform distribution to a uniform distribution, could be divided into three stages, i.e., thermal accumulation, thermal release, and thermal transfer. The concrete internal stress simulation indicated that the maximum tensile stress occurred at the stress concentration zone along the intersection of the circumferential pile foundation and was substantially affected by environmental temperature change. The maximum tensile stress value was 1 780.0 kPa, and the corresponding safety factor was 1.03, satisfying the design requirements. [Conclusions] A case study shows that the temperature gradient digital monitoring system successfully supports the dynamically adjusted temperature control and effectively controls the cracking risk. These study results can be used as a reference for the cracking control of similar projects.
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Intelligent cooling control of roller-compacted concrete dam during dam gap diversion
LI Ming, LIN Peng, LI Zichang, LIU Yuanguang, ZHANG Rui, GAO Xiangyou
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1060-1067. DOI: 10.16511/j.cnki.qhdxxb.2023.26.005
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Diverting flood via a dam gap or diversion tunnel is an economical and efficient method for the construction of a roller-compacted concrete (RCC) dam during the flood season. However, in the tropical climate of Africa, dam-gap diversion has a great influence on the dam temperature and stress field, which increases the risk of surface cracking. This paper analyzes dam temperature and stress evolution characteristics in high-temperature climatic conditions in tropical areas and develops a method for dam-gap intelligent temperature monitoring and feedback control. Relying on the Nyerere hydropower project, which has the largest installed capacity in East Africa, this paper adopts simulation, equipment development, and field application methods. A three-dimensional finite element model of the Nyerere hydroelectric dam during construction was established. The simulation boundary conditions were determined by the measured dam and river water temperatures. The dam gap concrete temperature and stress field were simulated under water pipe cooling conditions lasting for 0, 7, 14, and 21 d after pouring. After water pipe cooling, in the dam's elevation (EL) 77.0—95.0 m area, the temperature of the overwater surface concrete was not affected remarkably, but the internal temperature of the dam was remarkably reduced. The tensile stress on the overwater surface of the dam gap increased rapidly within a few days after the start of dam-gap diversion. The tensile stress continued to increase gradually and reached a peak at the end of the dam gap diversion. Furthermore, the self-developed intelligent temperature control system 2.0 was used to monitor and control dam body temperature throughout the dam-gap diversion period and to dynamically adjust the cooling strategy. The main findings were as follows: (1) This article revealed the temperature and stress field evolution characteristics of the dam under different water cooling schemes during the dam-gap diversion stage. A large temperature gradient was generated in the area within 3 m of the overwater surface. The maximum surface temperature stress without water cooling measures reached 2.04 MPa, which exceeded the allowable tensile stress. The risk of cracking could be effectively reduced by reducing the internal temperature of the dam. (2) An intelligent temperature control strategy for hot climate conditions was proposed. It is recommended that the EL 77.0—95.0 m area of the dam was water pipe cooled for at least 7 d and that the temperature at 2 m below the water crossing surface was cooled to <34.0 ℃ before dam-gap diversion. (3) An intelligent cooling control system 2.0 was developed. This system could intelligently regulate the cooling water temperature and flow supply and change the cooling water flow direction at regular intervals. It could effectively improve the concrete cooling effect, reduce the cooling energy consumption, and cool the dam temperature to the target temperature range before dam-gap diversion. The post-flood inspection detected no temperature cracks. It is indicated that the combination of temperature control simulation and the intelligent cooling control system 2.0 can effectively solve the temperature cracking problem in dam gaps. The study is of great significance for preventing RCC dam gaps from temperature cracks and can be used as a reference point for similar projects.
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Adaptive sliding mode control of underwater manipulator based on nonlinear dynamics model compensation
FU Wen, WEN Hao, HUANG Junhui, SUN Binxuan, CHEN Jiajie, CHEN Wu, FENG Yue, DUAN Xingguang
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1068-1077. DOI: 10.16511/j.cnki.qhdxxb.2023.26.025
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[Objectives] The South-to-North water diversion project is a strategic project in China. Since its construction, it has become the main source of water conservancy in more than 280 cities.The diversion tunnel is the key building to support the South-to-North water diversion project. Due to its long line, large diameter, high water pressure, complex surrounding rock geology, as well as many years of water conservancy erosion, biochemical substances erosion, geological effect and other influences, typical defects such as cracks, collapse, exposed steel bars are prone to occur. Artificial detection of defects in the tunnel not only consumes time and energy, but also has low accuracy and timeliness. Therefore, underwater robot inspection technology has become a hotspot of current research.Among them, the underwater manipulator can not only be installed on the underwater vehicle, but also can be selectively installed on the required platform to complete the tasks of cleaning the water surface, laying and repairing cables, salvaging sunken objects, cutting off ropes and so on. However, the control of the underwater manipulator is more complicated and difficult due to its time-varying mechanics, nonlinear properties, external interference and hydrodynamic influence. The main purpose of this paper is to establish the dynamics model of the underwater manipulator and improve the accuracy of the trajectory tracking of the manipulator. [Methods] In this paper, a modeling method combining Newton-Euler equation and Morrison's dynamic model is proposed, and then the dynamic parameters are identified. Then, in order to improve the precise control ability of the manipulator in complex transient underwater environment, an adaptive sliding mode control method is designed based on compensating nonlinear dynamics model and using radial basis function (RBF) neural network to compensate the unmodeled and modeling errors of the system. Through the dynamic modeling in Section 4, a detailed dynamic simulation environment of the underwater manipulator is obtained. Gaussian noise errors with amplitudes of 5, 20, 15, 10, 8, and 5 N·m are set for each joint. On this basis, Experiment 1(P1): double loop proportional integral differential (PID) controller is designed for control simulation. Then, in experiment 2(P2), RBF neural network is used to make fitting compensation for system modeling errors and unmodeled items. In experiment 3(P3), dynamic model compensation is added on the basis of P2. [Results] The trajectory tracking effect ratio of P2 and P3 was obviously better than that of P1 experiment, and the tracking effect of P3 experiment was also better than that of P2 experiment after compensating the dynamic model. [Conclusions] Through simulation, this paper has proved the effectiveness of the proposed hydrodynamic modeling of the manipulator, and on the basis of compensating nonlinear dynamic model, The adaptive sliding mode control method using RBF neural network to compensate the unmodeled and modeling errors of the system has higher trajectory tracking accuracy than the traditional PID control and the general RBF network adaptive sliding mode control.
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A real-time detection method for concrete dam cracks based on an object detection algorithm
HUANG Ben, KANG Fei, TANG Yu
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1078-1086. DOI: 10.16511/j.cnki.qhdxxb.2023.26.013
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As a major part of water conservancy infrastructure, dams play an important role in economic construction and social development. Cracks are one of the most common types of damage to dams, destroying the overall structure and affecting the durability, strength, and stability of the structure. Therefore, regular and systematic crack detection of concrete dams is of great importance to ensure their safe and stable operation. However, the traditional concrete dam crack detection technology suffers from slow speed, low precision, and insufficient generalization performance, bringing difficulty in meeting the requirements of concrete dam crack detection. Therefore, the objective of this study is to develop an efficient, accurate, and real-time concrete dam crack detection technology. Existing crack detection methods based on semantic segmentation algorithms run slowly and detect concrete cracks in real time with difficulty. In addition, the dam operation environment is harsh, resulting in complex image backgrounds and inconspicuous crack image features, increasing the difficulty of identification. This study proposes a real-time detection method for concrete dam cracks based on deep learning object detection method you only look once x (YOLOX), called YOLOX-dam crack detection (YOLOX-DCD), to address the problems of slow speed, low accuracy, and insufficient generalization of the traditional detection techniques for concrete dam cracks. This method improves the performance of YOLOX to detect concrete dam cracks. First, a lightweight convolutional block attention module (CBAM) is added to the network structure, which integrates the spatial attention mechanism with the channel attention mechanism. The CBAM makes the network pay more attention to crack features and improves detection performance. Second, a complete intersection over union (CIoU) is introduced to replace IoU as the loss function. The CIoU incorporates the normalized distance between the predicted box and the target box and summarizes three geometric factors in bounding box regression, i.e., overlap area, central point distance, and aspect ratio, thereby improving the convergence speed and detection performance of the algorithm. The experimental evaluation was conducted on a self-made concrete dam crack dataset. Ablation experiments were performed on each improved module, and the results showed that the improved method proposed in this paper effectively improved the detection accuracy of the model and maintained a high detection speed. The proposed model had an AP
0.5
on the test set of 90.84% and an F
1
of 87.74%, which were higher than those of various existing object detection methods. The FPS of the model was 65, and the detection speed was faster. The model was small, with a size of 25.67 MB, and could be deployed on a mobile terminal for real-time crack detection. In this study, a CBAM and the CIoU loss function are added to the YOLOX network, which make the network pay more attention to crack characteristics and improves the detection performance for concrete dam cracks. Experiments reveal that the method in this paper has fast speed, high precision, and few parameters and is obviously better than the classical object detection algorithms. Therefore, the proposed method meets the requirements of efficient, accurate, and real-time crack detection of concrete dams and is promising for providing a technical means for crack detection.
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Scour dynamic properties and online monitoring of offshore wind power foundation
WANG Xin, LIN Peng, HUANG Haodong, YUAN Jing, QIU Xu, LIU Xin
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1087-1094. DOI: 10.16511/j.cnki.qhdxxb.2023.26.007
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Because of favorable wind resource conditions and a lack of land occupation limitations, offshore wind power has been gaining an increasingly important role in the global energy strategy. However, scour is a widespread problem around offshore wind power foundations, resulting in a decrease in foundation bearing capacity, changes in structural natural frequency, and submarine pipeline exposure. As a result, monitoring and early warning of scour are essential. This study studied the scour process and its dynamic characteristics before proposing a method for identifying the scour initiation in design. For scour monitoring, multibeam sonars, the most often used scour measurement method, have problems of high cost and discontinuous operation, making it impossible to provide on-site scour data in a timely manner. Herein, a method for scour monitoring using structural vibration frequency is proposed. Then, based on ABAQUS, an integrated model of a wind turbine tower foundation was established to study the correlation between the scour depth and the first-order natural frequency, and the feasibility of using the structural vibration frequency to estimate the scour depth. As a result, a scour monitoring method and system based on low-frequency vibration data were developed. The data is acquired in real time by vibration sensors installed in specific parts and processed using a fast Fourier transform after data filtering to obtain the time-domain and frequency-domain characteristics necessary to determine whether the scour is normal. The numerical simulation results revealed that the first-order frequency of the structure was basically linear with the scour depth and that the frequency decreased by 0.009 3 Hz (3.3%), 0.017 2 Hz (6.3%) and 0.027 0 Hz (10.2%) for the scour depths of 3.0 m, 6.0 m and 9.0 m, respectively, compared to the scour-free condition (0.281 2 Hz). The monitoring data from an offshore wind farm in Jiangsu revealed that: (1) The installation orientation and height of the vibration sensors had essentially little effect on the first-order frequency; however, the vibration amplitude decreased as the installation elevation drops. (2) The variations of scour depth and frequency were basically consistent with the numerical results: the scour depths of turbine units #7, #15 and #17 increased from 3.47 m, 5.21 m and 6.11 m in September 2019 to 5.12 m, 5.48 m and 6.95 m in April 2020, while their vibration frequencies decreased from November 2019 to July 2020 by 0.001 3 Hz, 0.001 1 Hz and 0.002 3 Hz, respectively. Due to the lack of monitoring data, the frequency and scour depth do not fully correspond in time and space. There is an inconsistency between the change in frequency and scour depth of different units, but the monitoring data of all units show that the correlation between the two is clear. As a result, this paper suggests that when the frequency drops by more than 0.010 0 Hz in operation, the system will issue an early warning message prompting the cause of the accident to be investigated. The paper further discussed the future direction of the scour monitoring improvement, and the study results can be used as a reference for similar projects worldwide.
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Intelligent detection and numerical simulation analysis of concrete abrasion of astilling basin floor
WANG Haoran, XIE Hui, CHEN Yongcan, LIU Kang, LI Zhengwen, LI Yonglong
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1095-1103. DOI: 10.16511/j.cnki.qhdxxb.2023.26.022
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[Objective] The abrasion damage of hydraulic concrete is the main reason for the destruction of stilling basins. The long-term development of damage will threaten the safety of flood discharge in the flood season. Manual inspection is often used to evaluate the erosion condition of the stilling basin bottom plate in a project, which requires pumping and desilting. The inspection cost is high and cannot be determined during operation. Based on intelligent detection using a remotely operated vehicle (ROV), this research uses the abrasion evaluation method of the two-dimensional aggregate exposure ratio (AER) of hydraulic concrete to study the abrasion distribution of a stilling basin bottom, which has considerable application research value. [Methods] In this paper, the surface flow stilling basin of a large water conservancy project in Southwest China is taken as the study site. The detection equipment is a self-developed, ROV that has the functions of underwater crawling, floating, bottom plate dredging, and underwater acoustic positioning. The vehicle is equipped with a high-definition camera and can comprehensively detect the bottom plate abrasion damage of a stilling basin. According to the abrasion process of hydraulic concrete, an abrasion characteristic classification table is proposed, the abrasion damage degree is quantitatively characterized according to the AER, and the abrasion distribution of the bottom plate of the stilling basin is clarified. On this basis, the influence of hydrodynamic factors on the abrasion of the bottom slab of the stilling basin is further analyzed using three-dimensional numerical simulation. [Results] The results showed that: (1) The distribution law of the abrasion damage of the bottom plate of the stilling basin was basically consistent with the AER distribution. The AER could effectively reflect the abrasion damage of hydraulic concrete. (2) The abrasion in the front and rear sections of the stilling basin was severe, and there were different degrees of concrete mortar damage, aggregate exposure, falling off, and other undesirable phenomena. (3) The water flow in the stilling basin of the surface outlet fluctuateed violently, and the bottom velocity reached the maximum in the front area of the stilling basin; thus, this region was prone to scour, abrasion, and other damage. (4) Influenced by the tail sill of the stilling basin, the water flowed back in front of the tail sill, forming a vortex. The sand and stone deposition oscillated with the backflow vortex, continuously scouring the bottom plate of the stilling basin, resulting in an increase in the degree of abrasion in this area. [Conclusions] The AER can reflect the abrasion damage of the stilling basin bottom plate concrete to a certain extent and can be used to supplement the abrasion quantitative evaluation index system. The high flow velocity and backflow caused by sedimentation near the end sill are important factors leading to the erosion of the stilling basin floor. The research results have considerable application value and promotion importance for the safe operation and evaluation of a stilling basin structure.
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Design and detection efficiency analysis of desilting replacement module in sediment accumulation environment
LI Jialong, Chen Yongcan, LI Yonglong, WANG Haoran, XIE Hui
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1104-1112. DOI: 10.16511/j.cnki.qhdxxb.2023.26.004
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The drainage and energy dissipation building is an important aspect of the water conservation and hydropower project, and its structural safety is linked to the safety of the whole project. For a long time, the drainage and energy dissipation buildings have been subjected to the erosion of high pressure and high speed water, which will inevitably cause damage to the concrete structure. The apparent damage to underwater concrete structures is concealed due to the structure's uniqueness and diversity. The traditional method of diver inspection or manual inspection following cofferdam draining takes a long time and is expensive and dangerous. Using underwater robots for unmanned inspection reduces personal risk. However, the underwater robots' detection accuracy is limited due to the sediment accumulation on the bottom and poor visibility in the water, which makes it impossible to conduct timely investigations of defects and hidden dangers. This study has developed a desilting replacement module that is suitable for the conditions of sediment bottom and turbidity water and studied the mechanism design of the module, the efficiency of silt removal, and defect detection. The desilting replacement module is built in this study by examining the starting condition of sediment deposition and the features of the submerged water jet. It consists mostly of the desilting mechanism, the replacement detection mechanism, and the lifting mechanism. The Euler multiphase flow model was used to create the continuity equation and momentum equation of water and sand, and the hydrodynamic influence of the desilting replacement module was investigated. A simulation model based on Euler water-sand two-phase flow was developed using computational fluid dynamics software to mimic the desilting detection process of the desilting replacement module in the underwater sediment environment. The thickness of the sediment is considered to be 100 mm in the simulation, and the height of the sediment deposited at the beginning distance of the replacement detection shell was used as a variable to evaluate the status of the desilting replacement module when the detection effectiveness is optimal. Finally, the simulation findings are compared and examined by combining them with the real experimental data. This study verified the necessity of each mechanism in the desilting replacement module and concluded that when the initial height of sediment from the bottom of the replacement detection shell was 60 mm, the desilting detection efficiency was the highest, and the sediment of 100 mm thickness in the detection area could be removed to the remaining 10% within 1.56 s, and the total time of “desilting and detection” was 9.56 s. The silt removal replacement module's novel design tackles the underwater detection problems caused by underwater sediment accumulation and turbidity. The desilting replacement module may be carried on most existing underwater detection robots, which can significantly improve the detection ability of underwater robots in turbidity water environments. It can achieve short-term efficient single point or long-term continuous visual image acquisition in the sediment environment, depending on the operation requirements, which has a great promotion role for the application of underwater robot detection technology in the water conservation and hydropower industries.
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Shear strength of dam abutment fractured rock weakens critical water pressure and statistical damage constitutive model
XIE Hui, CHEN Ying, XIANG Yong, WANG Haoran, MA Fangping
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1113-1123. DOI: 10.16511/j.cnki.qhdxxb.2023.26.019
Abstract
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[Objective] The weakening of abutment rock strength under water-rock coupling has an important impact on the long-term safe and stable operation of high-arch dams. Under the joint action of prolonged arch thrust and high water pressure, the strength parameters of the rock in the weak interlayer of the dam abutment are reduced, which readily causes long-term stability problems such as structural instability, seepage damage, and bank slope sliding of the high dam hub. [Methods] Given the water pressure weakening effect of the shear strength parameters of the fractured marble at the dam abutment, the triaxial compression test of the fractured rock under the action of different seepage water pressures was performed using the rock mechanics testing system, and then the influence of seepage water pressure on the compressive strength, cohesion, and friction coefficient of the fractured rock was analyzed in combination with the rock stress-strain curve. Finally, the weakening critical water pressure of the rock was obtained by analyzing the effective stress principle. Furthermore, the statistical damage constitutive model of rock considering seepage pressure was studied. [Results] The results showed that the influence of seepage water pressure on the shear strength parameters of the fractured marble was mainly manifested by a weakening effect on cohesion. The weakening rate of cohesion increased substantially with increasing seepage water pressure, and the maximum weakening rate was nearly 100%. The weakened cohesion decreased linearly with increasing water pressure; when the weakening rate of cohesion was 0, the water pressure was the weakening critical water pressure. When the water pressure was lower than the critical water pressure, the water pressure weakening effect of rock strength was obvious, and the cohesion decreased linearly with increasing water pressure until vanishing; when the water pressure exceeded the critical water pressure, the rock strength decreased insubstantially with increasing water pressure, and the water pressure weakening effect of rock strength was not obvious. Based on the influence of seepage water pressure on shear strength parameters, a statistical damage constitutive model of rock considering the weakening effect of water pressure was constructed, and the adaptability and rationality of the theoretical model were verified using test data. [Conclusions] The critical water pressure, as the limiting value of the weakening of the rock strength and cohesion by the seepage pressure, can be used to define the influence of the seepage pressure on the rock strength. The statistical damage constitutive model considering the weakening effect of the seepage pressure can calculate the evolution law of the entire process of rock fracture under the water-rock coupling effect. The research results provide strong support for the theory and testing of water pressure weakening and have certain reference values and scientific significance for studying the weakening effect of fractured rock and analyzing the stability of high-arch dam abutments.
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Key technology and practice of intelligent underwater inspection in multiple scenarios of hydropower station
QI Ningchun, NIE Qiang, LAI Jitao, CHEN Yongcan, LI Yonglong
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1124-1134. DOI: 10.16511/j.cnki.qhdxxb.2023.26.016
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[Objective]Underwater building safety inspection is a vital tool for ensuring reservoir dam operation safety of hydropower stations. Due to the high expense of traditional drainage inspections and the high safety risk of divers performing underwater inspections for areas that cannot be drained, underwater detection technology provides a new solution to underwater building safety inspection. [Methods] Using the Yalong River basin step operation hydropower stations as a typical scenario, the target water environment and structural boundary conditions were analyzed; combined with open water underwater inspection experience and technical differences, underwater robot inspection equipment and essential technology systems under various scenarios of hydropower stations were constructed. Through robot system integration and testing, a small-sized, powerful, multi-sensor fusion cable remote control submersible was developed for tunnel-like structures with lengthy cavern lines. A high-strength, zero buoyancy photoelectric composite umbilical cable with a small diameter was designed, and remote power supply and fiber optic real-time communication were carried out through high-frequency medium voltage transmission technology. The real-time monitoring system for underwater robot movement based on the virtual exercise platform was built, and the robot was directed to return autonomously by an adaptive control algorithm in the case of communication and power supply failure. The combined inertial navigation-based positioning technology was investigated, and the position information, such as structural seams and feature markings detected by sonar and camera, was used to calibrate the inertial guidance positioning information. A high-frequency three-dimensional real-time sonar system with 360° mobility, continuous scanning, and real-time generation of a three-dimensional point cloud model was jointly developed, which improved precise positioning capability and detection efficiency for large cross-sections and long-distance closed structures. The research offers a defect identification technology based on dynamic feature distillation to intelligently identify the inspection images and uses the joint analysis method of inspection information and a 3D digital model to conduct intelligent spatiotemporal correlation analysis of defect information. Intelligent unmanned vessel systems and RTK-GNSS combined positioning technology are introduced for underwater inspection in semi-open waters in high mountain canyon areas. A joint inspection scheme of multibeam sonar and underwater robots is proposed to make full use of the advantages of fast and high-density scanning of multibeam sonar and fine inspection of robots to improve inspection efficiency. [Results] The robot system successfully passed through the access channel with only 2.1 m in diameter, the diversion tunnel with 12.0 m in diameter and 2.30 km in length, and the pressure pipeline with a 250.0 m vertical drop in the practice of normalized underwater inspection of multi-water scenes at Yalong River Basin Hydropower Station. The flaw detection accuracy reached the millimeter level, the plane positioning precision reached 10 cm, and the axial positioning accuracy was better than 1‰ of the traveled distance. The intelligent recognition rate of common defects in concrete structures, such as broken or exposed bars and cracks, reached 96.5%. The intelligent unmanned vessel successfully inspected various types of semi-open waters, such as tailwater channels of hydropower stations with a flow speed of 2 m/s and turbulent flows, obtaining three-dimensional topographic maps of underwater environments and identifying the distribution characteristics of underwater defects with a horizontal positioning accuracy better than ±8 mm+1 ppm and a vertical orientation better than ±15 mm+1 ppm. [Conclusions] The underwater intelligent inspection system features a high degree of innovation and integration, a large number of practical cases, safe and reliable inspection, and accurate and intuitive results. The system has effectively guided the safe operation and maintenance of underwater structures at the Yalong River Basin Hydropower Station and significantly reduced the cost of traditional inspection, which has important significance for industry promotion.
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Semantic segmentation method of hydraulic structure crack based on feature enhancement
CHEN Bo, ZHANG Hua, CHEN Yongcan, LI Yonglong, XIONG Jinsong
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1135-1143. DOI: 10.16511/j.cnki.qhdxxb.2023.26.009
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[Objective] Scientific, comprehensive, and standardized health monitoring is critical in the operation and maintenance of all types of water conservancy infrastructure. In this study, intelligent equipment is used to capture crack images of concrete dams and corridor hydraulic engineering scenes, and an artificial intelligence algorithm is used to achieve accurate recognition of crack information. However, most current research on concrete crack recognition lacks the analysis of crack information and simply obtains crack features through convolution and pooling to form a feature extraction network. The extracted high-dimensional features are not enhanced further, so the recognition effect cannot be continuously improved. A semantic segmentation technique for feature enhancement is proposed to solve the problem of low accuracy of crack location in the automatic detection of concrete cracks. [Methods] Statistical theory is used in this study to assess the pixel values of the cracked and non-cracked regions in three color channels and the proportion of the cracked region in the image. The size relationship and corresponding distribution of cracked and non-cracked regions on the pixel level are also obtained. Then, the ResNet-152 feature extraction network based on the residual structure is used to extract high-dimensional abstract semantic features from crack images. Due to the particularity of the residual structure, it can effectively reduce the loss of crack information during feature transmission and improve feature interoperability between different layers of the network so as to avoid the problem of gradient disappearance or explosion. Then, based on the results of statistical analysis, high-dimensional abstract features are sampled into two coarse segmentation feature maps corresponding to cracks and non-cracks. The similarity between the high-dimensional abstract features and the coarse segmentation feature map is calculated, the results of which are then used as weights to update high-dimensional abstract features to realize regional clustering of them. Finally, the clustered features are combined with the high-dimensional abstract features to obtain the enhanced features, which improve the crack location performance of the model. Meanwhile, the network loss function is optimized based on the crack information distribution. By controlling the number of samples used in the calculation of loss value, the contribution rate of crack information and non-crack information to the total loss value is balanced. As a result, the recognition accuracy of crack information is improved. [Results] We used an unmanned aerial vehicle and an orbital robot to capture images of two hydraulic engineering scenes, including the dam and the corridor. After image preprocessing and labeling, we obtained a total of 3 000 crack images and labels, including 1 000 dam crack images and 500 corridor crack images. We stratified the data set into a training set, a validation set, and a test set in an 8∶1∶1 ratio. The crack pixel accuracy, recall rate, intersection-over-unions, and overall total pixel accuracy of the model on the test set reached 92.48%, 86.52%, 80.82%, and 99.79%, respectively. [Conclusions] By analyzing the relationship and distribution of pixel values between crack information and non-crack information in crack images and using them as prior information to construct a feature enhancement network and design the objective function of network optimization, the shortcomings of current concrete crack identification methods can be effectively overcome, and the performance of the network to recognize crack information can be improved.
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Concrete image enhancement method for underwater uneven illumination scenes
LIN Haitao, WANG Haoran, LI Yonglong, CHEN Yongcan, ZHANG Hua
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1144-1152. DOI: 10.16511/j.cnki.qhdxxb.2023.26.011
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[Objective] Identifying concrete surface defects in underwater infrastructure is crucial to ensure safe and stable operation. At present, using ROV to gather concrete surface images is the most effective measure for underwater image detection. However, the concrete images obtained by ROV have some phenomena, such as uneven illumination, color imbalance, poor contrast, and weak edge information. In this study, the issue of underwater concrete photos with poor image quality in nonuniform lighting scenarios is investigated, and a method for underwater concrete image enhancement is suggested, which provides efficient data support for the detection and analysis of concrete surface defects in underwater infrastructure. [Methods] The local highlight issue caused by the fill light spots in underwater images is processed based on image repair. First, the image is thresholded, and the highlighted pixel area of the image is retained. Second, using the hough circle detection method, the annular fill light spot area on the image is retrieved. The resulting annular fill light spot image is then used as the Mask image of the original image for restoration. Finally, the local highlighted area caused by the fill light spot is repaired by filling the adjacent pixel area. An improved dark channel prior (DCP) technique is used to enhance the image to address the issue of poor image quality brought by the undersea environment’s uneven illumination. However, the single window size will have the following three problems: (1) A small size window area will lead to the oversaturation of local areas in the enhanced image. (2) A large window size can better eliminate the haze of the image but may produce halos. (3) A single-sized window is difficult to adapt to different pixel size images. Therefore, the selection area of the dark channel window size is expanded upon in this work using the contrast perception method. Image enhancement is done in each local window region by computing the contrast of seven neighborhood windows of one pixel and choosing the relevant dark channel window size following the contrast of the windows. [Results] To confirm the effectiveness of the algorithm, the image enhancement method suggested in the manuscript was compared with low-light underwater images using local contrast and multiscale fusion (L
2
UWE), relative global histogram stretching (GRHS), underwater light attenuation prior (ULAP), image blurriness and light absorption (IBLA), dark channel prior (DCP), and contrast limited adaptive histogram equalization (CLAHE). Simultaneously, four metrics, natural image quality evaluator (NIQE), perception-based image quality evaluator (PIQE), blind/reference less image spatial quality evaluator (BRISQUE), and underwater color image quality evaluation (UCIQE), were used to assess the enhanced images. Experiment results showed that the PIQE, BRISQUE, and UCIQE of the proposed method obtained scores of 25.75±3.93, 29.39±1.80, and 1.04±0.01, respectively, which performed best. [Conclusions] The proposed image enhancement method achieves balanced enhancement of images in terms of color, contrast, and brightness, and the algorithm in this paper can successfully enhance the quality of underwater images. Our study will aid in measuring underwater concrete fault levels.
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Dam surface crack detection method based on improved DeepLabV3+ network
ZHOU Xun, LI Yonglong, ZHOU Yingyue, WANG Haoran, LI Jiayang, ZHAO Jiaqi
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1153-1163. DOI: 10.16511/j.cnki.qhdxxb.2023.26.006
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Image analysis is an efficient and accurate method for identifying hydropower dam surface defects. However, due to the complex background of dam crack images and the uneven proportion of cracks and background pixels, the detection effect of traditional algorithms is poor. Moreover, traditional artificial crack inspection is not only inefficient but also costly in the present day. Efficient and accurate dam surface crack detection techniques are crucial for dam maintenance and operation. In order to achieve accurate and efficient dam surface crack detection, a dam surface crack detection method based on an improved DeepLabV3+ model is proposed. Model training is carried out for the self-made dam surface crack image dataset of a hydropower station in Southwest China, and the model is evaluated by
F
1,score
,
Z
MIoU
,
Z
MPA
, parameter quantity and other indicators. The following improvements are made to the traditional DeepLabV3+ network model: (1) A three line attention module is added to improve the model's ability to extract crack pixels and reduce proportion imbalance between background pixels and crack pixels. (2) The original pyramid pooling module is cascaded for model optimization so that the model can achieve more intensive pixel sampling, and subsequently obtain more abundant crack features. (3) In order to solve the problem of the significant/too large number of traditional DeepLabV3+ network parameters, MobileNetV2 network is used as the backbone of the model to extract the network, to reduce the network to a lightweight module, and to reduce model parameters. (4) Focal loss and Dice loss are used as the loss functions of the model to overcome the data imbalance and to improve the accuracy of network classification. The improved DeepLabV3+ network model in this paper could better realize the extraction of crack pixels, reduce the problems caused by the imbalance of pixel proportion, and better ensure the efficient and accurate detection of dam surface cracks. The experiment on the self-made dam surface crack image dataset of a hydropower station in Southwest China showed the following: (1) Compared with the original model, the improved DeepLabV3+ model increased
F
1, score
by 3.33%,
Z
MIOU
by 2.89%,
Z
MPA
by 1.12%, and the parameters were reduced to 3 014 714. This finding showed that the improved model proposed in this paper had stronger performance than the original model, better ability to extract crack pixels, and could better complete the task of crack identification. (2) Compared with other attention mechanisms, the three line attention module proposed in this paper had certain advantages, which could increase the attention of the model to the crack pixels and enable the model to extract the crack features needed. Through an analysis of the experimental results, the model improved in this paper has stronger segmentation ability, less missing data and false detection, and can effectively complete the dam surface crack segmentation task. The improved method increases the efficiency and accuracy of dam surface crack detection and reduces the model parameters. It can provide powerful data support for crack detection and the safe operation of hydropower projects.
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Monitoring and analysis of the auxiliary contact bounce of a gas-insulated switchgear circuit breaker according to transient voltage
ZHANG Pengfei, DING Dengwei, YANG Xinzhi, LIU Yan, LI Xing, HE Liang
Journal of Tsinghua University(Science and Technology). 2023,
63
(7): 1164-1172. DOI: 10.16511/j.cnki.qhdxxb.2023.26.012
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Gas-insulated switchgear (GIS) circuit breakers (CBs) with a closing resistor are characterized by structural complexity and a high failure rate. The auxiliary contact of the closing resistor may bounce during the closing process of the GIS CB. The bounce of the closing resistor contacts may cause arc restriking between the auxiliary contacts and aggravate the ablation of the contacts. Moreover, the auxiliary contact bounce may lead to the breakdown of the main break, resulting in high transient voltage and threatening the equipment insulation. Therefore, monitoring and evaluating the bounce of the auxiliary contact of the closing resistor is crucial. In this paper, the closing process of a CB with a closing resistor and the bounce of the auxiliary contacts were analyzed. Then, a method for monitoring and diagnosing the bounce condition of the auxiliary contact of the closing resistor according to the transient voltage during the closing process was proposed. An ultrawide-frequency-band sensing technology for transient voltage detection was introduced, and an online transient voltage-monitoring system based on the voltage divider sensing technology was realized. The effective measurement bandwidth of this system is 10 Hz-100 MHz. Two CBs (with and without a closing resistor) were used to charge the same gas insulated line (GIL), and the transient voltage during the CB closing process was monitored. The transient voltage and closing resistor contact bounce during the closing of two CBs were analyzed and compared, and the following conclusions were obtained. During the closing process of the CB without a closing resistor, the excited transient voltage contained rich high-frequency components. During the closing process of the CB with a closing resistor, two types of transient voltages (type Ⅰ and Ⅱ) were generated. Type Ⅰ did not contain any high-frequency components, and type Ⅱ was similar to the voltage generated during the closing process of the CB without a closing resistor. The type Ⅰ voltage was induced by the breakdown between the auxiliary contacts, and the type Ⅱ voltage was generated by the breakdown between the main contacts during the bounce of the auxiliary contacts. Through the online monitoring of the transient voltage during the CB closing process, the bounce of the auxiliary contacts and the breakdown voltage of the main break were analyzed, and the time interval between the first breakdown of auxiliary contacts and arc extinction after the bounce was proposed to characterize the bounce condition of the auxiliary contacts. Owing to the existence of a closing resistor, there is a difference between the transient voltages generated by the breakdown of the auxiliary break and the main break. During the closing process of the CB with a closing resistor, the breakdown occurred in the main break, indicating that the auxiliary contact bounced and that the closing resistor did not function. Therefore, through analysis of the moment at which the second type of transient voltage appears during the closing process of CBs with a closing resistor, the online monitoring and diagnosis of the bounce condition of the closing resistor contact could be realized. The results of this study can guide the effective monitoring and evaluation of the operating condition of CBs and provide a reference for the design and online monitoring of CBs with closing resistors.
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