An integrated method for evaluating and predicting long-term operation safety of concrete dams considering lag effect

Li, Mingchao; Si, Wen; Ren, Qingying; Song, Lingguang; Liu, Han

doi:10.1007/s00366-020-00956-6

Cited by 20 publications

(8 citation statements)

References 32 publications

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“…It many years since process modelling become an advanced tool for design work in many companies. Process plant model objectives include to provide a comprehensive report of materials and energy streams, determine the correlation between process units study the formation and separation of byproducts and impurities, support preventive maintain by tracking performance of key equipment over time and its relation to the buildup of impurities [6]- [9].…”

Section: Process System Formationmentioning

confidence: 99%

Process system integration

Stevanovic¹

2023

IJRIAS

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Process engineering today is concerned with the understanding and development of systematic procedures for design and optimal operation and control of the chemical process systems. This work motivated by the need to provide a more flexible than existing approaches framework for changes in chemical process engineering in particular, and for predicting the behavior of process systems in general. Integrated method of the process systems development make possible seeking out the most adequate model for simulation of real process design and optimization, that leads to improving current and development a new processes. The study state plant simulation model and dynamic simulation model make significant tools for observation behavior of the process. Comparative study of different processes can established more concurrent process alternatives.

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Section: Process System Formationmentioning

confidence: 99%

Process system integration

Stevanovic¹

2023

IJRIAS

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“…Among them, displacement is the most direct and comprehensive indicator of the service status of a concrete dam. By analyzing historical monitoring data, a data-driven dam displacement model can be established and used to predict future displacement (M. Li, Shen, Ren, & Li, 2019;M. Li, Si, Ren, Song, & Liu, 2020).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…Among them, displacement is the most direct and comprehensive indicator of the service status of a concrete dam. By analyzing historical monitoring data, a data‐driven dam displacement model can be established and used to predict future displacement (M. Li, Shen, Ren, & Li, 2019; M. Li, Si, Ren, Song, & Liu, 2020). An early warning of safety hazards may be generated when the difference between the actual measured displacement value and the model‐predicted value exceeds a predefined threshold.…”

Section: Introductionmentioning

confidence: 99%

A robust prediction model for displacement of concrete dams subjected to irregular water‐level fluctuations

Ren

et al. 2021

Computer aided Civil Eng

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Monitoring and predicting the displacement of concrete dams is one of the most crucial considerations for ensuring their long-term safe operation. Most existing models are designed for dams subjected to common structural and environmental conditions, with little attention paid to atypical operational conditions, such as structural strengthening or sudden changes in the external environment. The motivation for this work is to develop a reliable prediction model for displacement behavior of concrete dams subjected to irregular upstream water-level fluctuations. In our study, a reconstruction method for unevenly sampled time series is presented to analyze such data. Then, an improved model, factor weighted support vector regression (FWSVR), which differentiates various factors and their effects through a weighting matrix, is theoretically derived. The weights are determined by the RReliefF algorithm, and together with FWSVR form the final RReliefF-based FWSVR (RFWSVR) model. In particular, the hyperparameters involved in the above modeling strategy are optimized by the Grey Wolf Optimizer. Eventually, the prediction robustness of the developed model was verified on the data from four representative monitoring points of a real-world dam, where its accuracy was compared to classical dam behavior modeling methods, FWSVR models using other weighting methods, and an ensemble learning algorithm. Comparative evaluation of the performance of the different methods was conducted with the help of recognized statistical indices. The evaluation results show that the overall performance of the proposed RFWSVR model is optimal for the displacement prediction at the selected points when the dam case is subjected to irregular water-level changes. This novel modeling approach may be generalized for modeling the evolution behavior of other civil or hydraulic structures.

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“…Numerical simulation [10][11][12][13] and observational investigation [14][15][16][17] are the two most representative methods for analyzing the macroscopic performance of concrete dams involving fractures, considering the dimensional inconsistency between laboratory experiments and practical engineering. With the incorporation of extended fnite element method (XFEM) [18][19][20], virtual crack closure technique (VCCT) [21][22][23], and cohesive interface elements [24,25], a series of computational methods have been proposed to reveal the service conditions of concrete dams in jeopardy cracking.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation Method of Crack Variation on Structural Performance of Concrete Dams with Fusion Entropy Based on Observation and Simulation

Qin

Yuan

et al. 2023

Structural Control and Health Monitoring

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This study proposes a method for evaluating crack variations on structural performance of concrete dams using observational and computational output. The structural performance is represented by the system entropy in concrete dams, and the stress-strain field is established by incorporating observations and simulations for entropy calculations. Considering the characterization ability of the sample points, the weighted entropy sequence is constructed with a selected index system. Thereafter, the weighted fusion entropy is successively separated and analyzed with rescaled range (R/S) analysis, and the Hurst exponent difference and corresponding warning indicators are calculated to quantify the destructiveness of the crack variation. The application of the presented method is elaborated in a concrete arch dam, and the behavior of J01-crack exhibits no significant destructiveness on its structural condition. The analysis results verified the feasibility of the proposed method in destructiveness evaluation of crack behavior on the structural performance of concrete dams.

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An integrated method for evaluating and predicting long-term operation safety of concrete dams considering lag effect

Cited by 20 publications

References 32 publications

Process system integration

Process system integration

A robust prediction model for displacement of concrete dams subjected to irregular water‐level fluctuations

An Evaluation Method of Crack Variation on Structural Performance of Concrete Dams with Fusion Entropy Based on Observation and Simulation

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