Monitoring high concrete dams during their construction and service

During the construction of concrete dams from rolled-compacted concrete, the main effect on the structure are the temperature effects. As a result of heat generation during hydration of cement and the influence of many other factors, significant temperature gradients and cracks may occur. In this paper, the optimal maximum temperatures arising in the body of the concrete dam under construction are determined by the method of experiment planning and the method of numerical simulation - the finite element method. The analysis of the influence of the acting factors on the temperature regime and the thermal stressed state at the rock-built concrete dam from rolled concrete is carried out. The dependences are obtained and nomograms are constructed to determine the optimal parameters. With the help of the computer program Midas Civil 2011, calculations of the temperature regime of the constructed dam were carried out and the maximum temperatures were determined. The calculations of thermal stress state of the structure along with an analysis of the possible cracking are conducted.

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Seismic fragility analysis of concrete dams: A state-of-the-art review

Engineering Structures ◽

10.1016/j.engstruct.2016.09.034 ◽

2016 ◽

Vol 128 ◽

pp. 374-399 ◽

Cited By ~ 34

Author(s):

Mohammad Amin Hariri-Ardebili ◽

Victor E. Saouma

Keyword(s):

State Of The Art ◽

Fragility Analysis ◽

Seismic Fragility ◽

Concrete Dams

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Parameter identification of concrete dams using swarm intelligence algorithm

Engineering Computations ◽

10.1108/ec-03-2017-0110 ◽

2017 ◽

Vol 34 (7) ◽

pp. 2358-2378 ◽

Cited By ~ 6

Author(s):

Siqi Dou ◽

Junjie Li ◽

Fei Kang

Keyword(s):

Parameter Identification ◽

Swarm Intelligence ◽

Inverse Analysis ◽

Arch Dam ◽

Hydraulic Structures ◽

Concrete Dams ◽

Concrete Gravity Dam ◽

Element Analysis ◽

Content Type ◽

Fireworks Algorithm

Purpose Parameter identification is an important issue in structural health monitoring and damage identification for concrete dams. The purpose of this paper is to introduce a novel adaptive fireworks algorithm (AFWA) into inverse analysis of parameter identification. Design/methodology/approach Swarm intelligence algorithms and finite element analysis are integrated to identify parameters of hydraulic structures. Three swarm intelligence algorithms: AFWA, standard particle swarm optimization (SPSO) and artificial bee colony algorithm (ABC) are adopted to make a comparative study. These algorithms are introduced briefly and then tested by four standard benchmark functions. Inverse analysis methods based on AFWA, SPSO and ABC are adopted to identify Young’s modulus of a concrete gravity dam and a concrete arch dam. Findings Numerical results show that swarm intelligence algorithms are powerful tools for parameter identification of concrete structures. The proposed AFWA-based inverse analysis algorithm for concrete dams is promising in terms of accuracy and efficiency. Originality/value Fireworks algorithm is applied for inverse analysis of hydraulic structures for the first time, and the problem of parameter selection in AFWA is studied.

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