A probabilistic analysis method for gravity dam earthquake risk

Abstract

The invention discloses a gravity dam earthquake risk probability analysis method, specifically comprising the following steps: S1: Gravity dam dynamic finite element analysis and dam failure state discrimination under different earthquake motions; S2: Screening for gravity dam failure state prediction S3: Establish a BP neural network model to quickly predict the failure state of the gravity dam; S4: Select the ground motion records used to predict the failure state of the gravity dam, and calculate the earthquake intensity parameters; S5: Different PGA levels Gravity dam failure probability estimation; S6: draw the gravity dam seismic vulnerability curve; S7: calculate the gravity dam seismic risk probability; S8: evaluate the gravity dam seismic risk according to the calculated seismic risk probability.

Description

technical field [0001] The invention relates to the technical field of gravity dam seismic analysis, in particular to a gravity dam earthquake risk probability analysis method. Background technique [0002] Reservoir dams have multiple functions such as flood control, power generation, irrigation, and water supply, and are important infrastructure for the national economy. Concrete gravity dam (referred to as gravity dam) is one of the commonly used dam types in water conservancy and hydropower projects. Under the action of strong earthquakes, gravity dams may be damaged to varying degrees, which directly threatens the safety and normal operation of the project. Therefore, the seismic risk analysis and assessment of gravity dams in high seismic intensity areas has always been a matter of great concern to the industry and society. The probabilistic analysis of structural seismic risk can simultaneously consider the seismic hazard of the site and the seismic vulnerability of ...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a gravity dam earthquake risk probability analysis method, in view of the current gravity dam earthquake risk probability analysis method through numerical simulation to predict the structural failure state, the shortcomings of low calculation efficiency and long time consumption, and optimize the earthquake through correlation analysis The strength parameter, as the input parameter of the artificial neural network, uses the neural network to replace the time-consuming numerical simulation, realizes the rapid prediction of the failure state of the gravity dam, and significantly reduces the calculation workload

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