Thermal parameter inversion for various materials of super high arch dams based on the hybrid particle swarm optimization method
WANG Feng1,2, ZHOU Yihong1,2, ZHAO Chunju1,2, ZHOU Huawei1,2, CHEN Wenfu3, TAN Yaosheng3, LIANG Zhipeng1,2, PAN Zhiguo1,2, WANG Fang1,2
1. College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China; 2. Hubei Key Laboratory of Construction and Management in Hydropower Engineering, China Three Gorges University, Yichang 443002, China; 3. China Three Gorges Projects Development Co., Ltd., Chengdu 610041, China
Abstract：Concrete thermal parameters during construction and laboratory tests can differ, so the particle swarm optimization (PSO) algorithm and optical fiber temperature monitoring data were used to identify the thermal parameters of the concrete for super high arch dams at low winter temperatures. Traditional PSO algorithms can easily fall into local extrema, so a swarm intelligence-hybrid particle swarm optimization (HPSO) model was developed in this study using a concave function weight decreasing strategy to avoid local extrema. HPSO combines PSO with genetic algorithm cross and mutation operations. These more effectively balance the algorithm global and local search abilities. HPSO was used for thermal parameter inversion searches of various strength concretes and concretes with various gradations with cooling water and a specified environmental temperature. The model considers the influences of multi-stage water flows and water temperature variations along the cooling water pipe. Examples show the effectiveness of the intelligent identification system and the quick convergence of HPSO. The inversion results clarify the relationship between the thermal parameters and the temperature changes.
王峰, 周宜红, 赵春菊, 周华维, 陈文夫, 谭尧升, 梁志鹏, 潘志国, 王放. 基于混合粒子群算法的特高拱坝不同材料热学参数反演分析[J]. 清华大学学报（自然科学版）, 2021, 61(7): 747-755.
WANG Feng, ZHOU Yihong, ZHAO Chunju, ZHOU Huawei, CHEN Wenfu, TAN Yaosheng, LIANG Zhipeng, PAN Zhiguo, WANG Fang. Thermal parameter inversion for various materials of super high arch dams based on the hybrid particle swarm optimization method. Journal of Tsinghua University(Science and Technology), 2021, 61(7): 747-755.