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论文类型：期刊论文

发表时间：2020-01-01

发表刊物：JOURNAL OF STRUCTURAL ENGINEERING

收录刊物：EI、SCIE

卷号：146

期号：1

ISSN号：0733-9445

关键字：Dam behavior modeling; Displacements; Structural health monitoring; Temperature simulation; Gaussian processes

摘要：Structural health monitoring models provide important information for safety control of large dams. The main challenge in developing an accurate dam behavior prediction model lies in the modeling of extreme temperature effect. This paper presents a Gaussian process regression-based displacement model for health monitoring of concrete gravity dams, which can model the temperature effect by using long-term air temperature data. Important attractions of Gaussian processes include accurate simulation results, convenient training, and so forth. Different covariance functions and temperature variable sets are tested on the horizontal displacement prediction problem of concrete dams. Results show that segmented air temperature based Gaussian process regression models can reflect the extreme air temperature effect on displacements of concrete gravity dams, considering the prediction accuracy is much better than that of a mathematical model based on periodic functions. (C) 2019 American Society of Civil Engineers.