A Deformation Analysis Method for Sluice Structure Based on Panel Data

Author:

Ma Zekai12,Lou Benxing123,Shen Zhenzhong12,Ma Fuheng3,Luo Xiang123,Ye Wei3,Li Xing3ORCID,Li Dongze12

Affiliation:

1. The National Key Laboratory of Water Disaster Prevention, Hohai University, No. 1 Xikang Road, Nanjing 210024, China

2. College of Water Conservancy and Hydropower Engineering, Hohai University, No. 1 Xikang Road, Nanjing 210024, China

3. Department of Dam Safety and Management, Nanjing Hydraulic Research Institute, No. 223 Guangzhou Road, Nanjing 210098, China

Abstract

Deformation, as the most intuitive index, can reflect the operation status of hydraulic structures comprehensively, and reasonable analysis of deformation behavior has important guiding significance for structural long-term service. Currently, the health evaluation of dam deformation behavior has attracted widespread attention and extensive research from scholars due to its great importance. However, given that the sluice is a low-head hydraulic structure, the consequences of its failure are easily overlooked without sufficient attention. While the influencing factors of the sluice’s deformation are almost identical to those of a concrete dam, nonuniform deformation is the key issue in the sluice’s case because of the uneven property of the external load and soil foundation, and referencing the traditional deformation statistical model of a concrete dam cannot directly represent the nonuniform deformation behavior of a sluice. In this paper, we assume that the deformation at various positions of the sluice consist of both overall and individual effects, where overall effect values describe the deformation response trend of the sluice structure under external loads, and individual effect values represent the degree to which the deformation of a single point deviates from the overall deformation. Then, the random coefficient model of panel data is introduced into the analysis of sluice deformation to handle the unobservable overall and individual effects. Furthermore, the maximum entropy principle is applied, both to approximate the probability distribution function of individual effect extreme values and to determine the early warning indicators, completing the assessment and analysis of the nonuniform deformation state. Finally, taking a project as an example, we show that the method proposed can effectively identify the overall deformation trend of the sluice and the deviation degree of each measuring point from the overall deformation, which provides a novel approach for sluice deformation behavior research.

Funder

Modern Multimodal Transportation Laboratory Open Fund Project

Yellow River Water Science Research Joint Fund

National Natural Science Foundation of China

Publisher

MDPI AG

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