Intelligent cooling control of roller-compacted concrete dam during dam gap diversion
LI Ming1, LIN Peng1, LI Zichang2, LIU Yuanguang3, ZHANG Rui3, GAO Xiangyou4
1. Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; 2. Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu 610000, China; 3. Sinohydrd Bureau 11 Co., Ltd., Zhengzhou 450001, China; 4. TSCON(Wuhan) Technology Co., Ltd., Wuhan 430074, China
Abstract：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.
李明, 林鹏, 李子昌, 刘元广, 张睿, 高向友. 缺口导流期碾压混凝土坝智能通水温控[J]. 清华大学学报（自然科学版）, 2023, 63(7): 1060-1067.
LI Ming, LIN Peng, LI Zichang, LIU Yuanguang, ZHANG Rui, GAO Xiangyou. Intelligent cooling control of roller-compacted concrete dam during dam gap diversion. Journal of Tsinghua University(Science and Technology), 2023, 63(7): 1060-1067.
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2023, Vol. 63 
