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Morris Sensitivity Analysis for Hydrothermal Coupling Parameters of Embankment Dam: A Case Study

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  • Jie Ren
  • Wenbing Zhang
  • Jie Yang

Abstract

Recently, the use of the temperature tracer method has attracted a great deal of attention to study the dam leakage. Accurate estimation of temperature variations inside the dam is critical, and the task can be achieved by identifying which variables play more important roles in the hydrothermal coupling model (HTCM). In the present study, the HTCM of an embankment dam is defined based on the thermal conductivity model proposed by Lu et al. (2007). The thermal conductivity model needs several input parameters, many of which are usually determined by pedotransfer functions, which may introduce a certain degree of uncertainty. Using the Morris method, the embankment dam of a reservoir, located in Shaanxi province of China, was chosen as the case study to investigate the sensitivity of each parameter of the HTCM on the temperature field of the embankment dam. The sensitivity analysis showed that the hydraulic conductivity ( ) of HTCM has the highest effect on the dam temperature field. On the other hand, the saturated water content ( ), residual water content ( ), and porosity ( n ) only slightly influence the temperature estimation of the model. Accordingly, the effects of these three parameters on the heat conduction and the subsequent temperature field of the dam can be neglected. Results of this study showed that the model correction workload can be substantially reduced. Hence, the efficiency of the model correction procedure leads to reasonable selection of decision parameters and can be significantly improved by reducing the number of these parameters for the HTCM of the embankment dam.

Suggested Citation

  • Jie Ren & Wenbing Zhang & Jie Yang, 2019. "Morris Sensitivity Analysis for Hydrothermal Coupling Parameters of Embankment Dam: A Case Study," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-11, June.
  • Handle: RePEc:hin:jnlmpe:2196578
    DOI: 10.1155/2019/2196578
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    Cited by:

    1. Ruichen Xu & Yong Pang & Zhibing Hu & Xiaoyan Hu, 2022. "The Spatiotemporal Characteristics of Water Quality and Main Controlling Factors of Algal Blooms in Tai Lake, China," Sustainability, MDPI, vol. 14(9), pages 1-17, May.
    2. Doh Dinga, Christian & Wen, Zongguo, 2022. "Many-objective optimization of energy conservation and emission reduction under uncertainty: A case study in China's cement industry," Energy, Elsevier, vol. 253(C).

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