# Optimization Method for Improving Efficiency of Thermal Field Reconstruction in Concrete Dam
###### Abstract  
In an actual concrete dam construction, the efficiency of thermal field reconstruction directly affects the timeliness of temperature control measures. Therefore, using lightweight methods to obtain real-time, accurate thermal fields is crucial for concrete temperature control. To balance both accuracy and efficiency, this study proposes an optimization method for thermal field reconstruction in concrete dams. The method consists of three components: evaluating interpolation algorithms, optimizing the number of monitoring points, and analyzing their positions. Specifically, a distributed temperature sensing system is employed for concrete monitoring, with a \"Z-shaped\" optical fiber layout. Three interpolation algorithms--Kriging, Natural Neighbor, and Inverse Distance Weighting--are quantitatively evaluated, with Kriging showing the highest accuracy. Sensitivity analysis, combined with the control variable method, is used to assess the impact of the monitoring point number and position. Lightweight application procedures are then proposed, using reconstructed thermal field results to guide strategy formulation and parameter adjustment for the intelligent cooling control system. A case study demonstrates that this method ensures the effectiveness and timeliness of concrete temperature control measures. The proposed approach enables real-time updates of concrete temperature control measures in sync with the progress of the pouring process, providing a valuable reference for similar projects. thermal field reconstruction; optimization method; interpolation algorithm; temperature control; concrete dam +
Footnote †: journal: applied sciences  
0000-0001-680-7822-3333-333-333  
and flow rate [6]. However, variations in pouring schedules, spatial positions, and constraints lead to significant differences in temperature distribution across concrete blocks [7]. To ensure effective water-cooling, personalized adjustments based on each block's actual temperature are essential [8]. The efficiency of thermal field reconstruction directly affects temperature control. Thus, an efficient, real-time, and accurate method for thermal field reconstruction is crucial for optimizing temperature control strategies in concrete dams. Thermal field reconstruction methods for concrete dams can be categorized into three types. The first is the analytical method by solving the heat diffusion equation [9]. Since its inception, the method has been continuously improved and applied in engineering projects [10; 11]. The analytical method has clear physical significance [12], but assumptions about the geometry and boundary conditions of concrete blocks may lead to errors. The second method is numerical analysis [13; 14]. For example, numerical simulations were conducted to analyze the differences in surface-insulation measures [15]. Numerical analysis methods face challenges such as parameter discrepancies [16], long computation time, and inefficiency [17]. In large-scale simulations with fine meshes, thermal field reconstruction lags, making it difficult to adjust temperature control measures in real time [18]. The third method relies on real monitoring data for interpolation calculations [19]. After collecting substantial monitoring data, interpolation algorithms enable thermal field reconstruction [20; 21]. For example, the combination of interpolation algorithms with the distributed temperature sensing (DTS) system has enabled the acquisition of concrete thermal fields [22; 23]. Recent improvements such as optimizing monitoring point locations [24] and identifying valid temperature-measuring optical fiber [25] have further enhanced this method's practicality. As monitoring data update, interpolation methods can reveal the temporal variation of concrete temperatures in dams [26]. In engineering practice, achieving real-time temperature control for each concrete block requires balancing accuracy and efficiency in thermal field reconstruction.