journal article·2024-11-23Open access

Optimization Method for Improving Efficiency of Thermal Field Reconstruction in Concrete Dam

Yunfei Xiang, Peng Lin, Haoyang Peng, Zichang Li, Yuanguang Liu, Yu Qiao, Zuobin Yang

Applied Sciences· Volume 14· Issue 23

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Dam Engineering and Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China

Tsinghua Sichuan Energy Internet Research Institute, Chengdu 610213, China

Yalong River Hydropower Development Company, Ltd., Chengdu 610051, China

Sinohydro Bureau 11 Co., Ltd., Zhengzhou 450001, China

China Three Gorges Corporation, Beijing 100038, China

Huaneng Lancang River Hydropower Inc., Kunming 650214, China

Funding

China Three Gorges Corporation Research Program · Snohydro Bureau 11 Co., Ltd.’s Management Department of the Julius Nyerere Hydropower Station Project in the United Republic of Tanzania · China Huaneng Group Co., Ltd.’s Research Program

References (48)

Show source-provided references
1. Peng, H., Lin, P., Xiang, Y., Hu, J., and Yang, Z. (2022). Effects of carbon thin film on low-heat cement hydration, temperature and strength of the wudongde dam concrete. Buildings, 12.10.3390/buildings12060717 ↗
2. Mechanical properties, long-term hydration heat, shinkage behavior and crack resistance of dam concrete designed with low heat Portland (LHP) cement and fly ash10.1016/j.conbuildmat.2018.08.056 ↗
3. The influence of curing regimes on hydration, microstructure and compressive strength of ultra-high performance concrete: A review10.1016/j.jobe.2023.107401 ↗
4. Influence of curing temperature on the hydration and strength devel-opment of Class G Portland cement10.1016/j.cemconres.2022.106776 ↗
5. Study on the gallery structure cracking mechanisms and cracking control in dam construction site10.1016/j.engfailanal.2020.105135 ↗
6. Intelligent cooling control for mass concrete relating to spiral case structure
7. Žvanut, P., Turk, G., and Kryžanowski, A. (2021). Thermal analysis of a concrete dam taking into account insolation, shading, water level and spillover. Appl. Sci., 11.10.3390/app11020705 ↗
8. An ANN-based short-term temperature forecast model for mass concrete cooling control10.26599/TST.2022.9010015 ↗
9. Groz, M.-M., Bensalem, M., Sommier, A., Abisset-Chavanne, E., Chevalier, S., Chulkov, A., Battaglia, J.-L., Batsale, J.-C., and Pradere, C. (2020). Estimation of thermal resistance field in layered materials by analytical asymptotic method. Appl. Sci., 10.10.3390/app10072351 ↗
10. Cracking and thermal resistance in concrete: Coupled thermo-mechanics and phase-field modeling10.1016/j.tafmec.2024.104285 ↗
11. Klemczak, B., Smolana, A., and Jędrzejewska, A. (2024). Modeling of Heat and Mass Transfer in Cement-Based Materials during Cement Hydration—A Review. Energies, 17.10.3390/en17112513 ↗
12. Mesoscale modeling of concrete: Geometry and numerics10.1016/j.compstruc.2005.10.003 ↗
13. A study on thermal analysis of under-construction concrete dam
14. Mirković, U., Kuzmanović, V., and Todorović, G. (2022). Long-Term Thermal Stress Analysis and Optimization of Contraction Joint Distance of Concrete Gravity Dams. Appl. Sci., 12.10.3390/app12168163 ↗
15. Field test and numerical simulation of the thermal insulation effect of concrete pouring block surface based on DTS10.1016/j.conbuildmat.2022.128022 ↗
16. Wang, F., Zhao, C., Zhou, Y., Zhou, H., Liang, Z., Wang, F., Seman, E.A., and Zheng, A. (2023). Multiple Thermal Parameter Inversion for Concrete Dams Using an Integrated Surrogate Model. Appl. Sci., 13.10.3390/app13095407 ↗
17. Hu, J., Li, K., Wu, Y., Zeng, D., and Wang, Z. (2022). Optimization of the Cooling Scheme of Artificial Ground Freezing Based on Finite Element Analysis: A Case Study. Appl. Sci., 12.10.3390/app12178618 ↗
18. Chen, M., Liu, S., Sun, S., Liu, Z., and Zhao, Y. (2020). Rapid reconstruction of simulated and experimental temperature fields based on proper orthogonal decomposition. Appl. Sci., 10.10.3390/app10113729 ↗
19. Temperature field reconstruction of concrete dams based on distributed optical fiber monitoring data10.1007/s12205-019-0787-6 ↗
20. Real-time temperature field reconstruction using a few measurement points and RPIM-AGQ6 interpolation10.1016/j.measurement.2023.114041 ↗
21. Optimization of distributed optical fiber temperature monitoring points based on 3D temperature field reconstruction10.1016/j.tsep.2024.102741 ↗
22. A 3D thermal field restructuring method for concrete dams based on real-time temperature monitoring10.1007/s12205-021-1084-8 ↗
23. Feedback design of temperature control measures for concrete dams based on real-time temperature monitoring and construction process simulation10.1007/s12205-017-1935-5 ↗
24. Peng, H., Lin, P., Xiang, Y., Chen, W., Zhou, S., Yang, N., and Qiao, Y. (2020). A positioning method of temperature sensors for monitoring dam global thermal field. Front. Mater., 7.10.3389/fmats.2020.587738 ↗
25. Method and Application of Spatial Positioning for Valid Temperature-measuring Optical Fibers in Concrete Dams10.1007/s12205-023-2336-6 ↗
26. Temperature monitoring and simulation analysis of the bottom orifices of Baihetan arch dam when outflowing10.1016/j.icheatmasstransfer.2023.107200 ↗
27. Imanian, H., Shirkhani, H., Mohammadian, A., Cobo, J.H., and Payeur, P. (2023). Spatial interpolation of soil temperature and water content in the land-water interface using artificial intelligence. Water, 15.10.3390/w15030473 ↗
28. Improving sea surface temperature in a regional ocean model through refined sea surface temperature assimilation10.5194/os-19-729-2023 ↗
29. Interpolation, satellite-based machine learning, or meteorological simulation? A comparison analysis for spatio-temporal mapping of mesoscale urban air temperature10.1007/s10666-023-09943-9 ↗
30. Temperature Field Online Reconstruction for In-Service Concrete Arch Dam Based on Limited Temperature Observation Data Using AdaBoost-ANN Algorithm
31. Detecting pipeline leakage using active distributed temperature Sensing: Theoretical modeling and experimental verification10.1016/j.tust.2023.105065 ↗
32. Distributed optical fiber sensing system based on semiconductor lasers with mutual un-balanced double optical injection10.1016/j.ijleo.2023.170706 ↗
33. Development and analysis of a BP-LSTM-Kriging temperature field prediction model for the arch ring section of the reinforced concrete arch bridge10.1016/j.istruc.2024.106564 ↗
34. Comparison of inverse distance weighted and natural neighbor interpolation method at air temperature data in Malang region
35. Coupling random forest and inverse distance weighting to generate climate surfaces of precipitation and temperature with Multiple-Covariates10.1016/j.jhydrol.2021.126270 ↗
36. Measurement of Temperature through Raman Scattering10.1016/j.procs.2015.12.003 ↗
37. A review of previous studies on the applications of optical fiber sensors in geotechnical health monitoring10.1016/j.measurement.2014.08.013 ↗
38. Ma, Y., Zhang, Y., Cheng, Y., Zhang, Y., Gao, X., and Shan, K. (2022). A case study of field thermal response test and laboratory test based on distributed optical fiber temperature sensor. Energies, 15.10.3390/en15218101 ↗
39. Distributed optical fiber sensing based on Rayleigh scattering10.2174/1874328501307010104 ↗
40. Muanenda, Y., Oton, C.J., and Di Pasquale, F. (2019). Application of Raman and Brillouin scattering phenomena in distributed optical fiber sensing. Front. Phys., 7.10.3389/fphy.2019.00155 ↗
41. Application of distributed temperature sensing for cracking control of mass concrete10.1016/j.conbuildmat.2018.11.221 ↗
42. Experimental study on distributed optical fiber heated-based seepage behavior identification in hydraulic engineering10.1007/s00231-018-2431-2 ↗
43. Correlating variations in the dynamic power signature to nugget diameter in resistance spot welding using Kriging model10.1016/j.measurement.2018.11.025 ↗
44. The numerical analysis of symmetric cross-ply laminates using the natural neighbour radial point interpolation method and high-order shear deformation theories10.1016/j.engstruct.2020.111247 ↗
45. Surfer: A fast simulation algorithm to predict surface temperatures and mean radiant temperatures in large urban models10.1016/j.buildenv.2021.107762 ↗
46. Protasov, A. (2017, January 29–31). Reconstruction of the thermal field image from measurements in separate points. Proceedings of the 2017 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS), Kiev, Ukraine.10.1109/MRRS.2017.8075035 ↗
47. Comparison of several interpolation methods to reconstruct field data in the vicinity of a finite element immersed boundary10.1016/j.camwa.2022.08.002 ↗
48. RecFNO: A resolution-invariant flow and heat field reconstruction method from sparse observations via Fourier neural operator10.1016/j.ijthermalsci.2023.108619 ↗