Identification method of key risk factors and risk transmission key path of cascade hydropower station based on Bayesian risk network

A technology of risk factors and critical paths, applied in data processing applications, instruments, calculations, etc., can solve problems such as defects, hidden dangers, and uncertainties in engineering safe operation, and achieve good results in application prospects

Active Publication Date: 2022-04-08
SICHUAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Affected by objective uncertain factors such as natural conditions (geology, hydrology, climate, etc.), construction conditions (environment, traffic, rolling, etc.) and subjective uncertain factors in design, construction and procurement, hydropower project construction and During the operation process, new problems and challenges are constantly encountered, and quality defects or hidden dangers may appear in all stages of design, construction, and commissioning, which bring a lot of uncertainty to the safe operation of the project;

Method used

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  • Identification method of key risk factors and risk transmission key path of cascade hydropower station based on Bayesian risk network
  • Identification method of key risk factors and risk transmission key path of cascade hydropower station based on Bayesian risk network
  • Identification method of key risk factors and risk transmission key path of cascade hydropower station based on Bayesian risk network

Examples

Experimental program
Comparison scheme
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Embodiment

[0022] Taking a cascade hydropower station in the Dadu River Basin as an example, the dam type of the power station is an earth-rock dam, and the flood discharge structure consists of a tunnel spillway, a deep hole spillway and a shaft (very) spillway. Construct the Bayesian risk network of cascade hydropower stations, and obtain the Bayesian risk network under the initial conditions by calculating the prior probability and conditional probability (see figure 2 );

[0023] According to the method of the present invention, the key risk factors of cascade hydropower stations are identified as follows:

[0024] Step 1: Define "dam failure" as the target event;

[0025] Step 2: Calculate the amount of risk disturbance;

[0026] Dam overflow: (96.02%-1.15e-4%)×100=96.02

[0027] Dam mass: (1%-1.15e-4%)×100=1.0

[0028] Other abnormalities: (0.01%-1.15e-4%)×100=0.01

[0029] The third step is to compare the size of the risk disturbance. Obviously, "dam overflow" is the key ris...

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Abstract

The invention discloses a method for identifying key risk factors and risk transfer key paths of cascade hydropower stations based on a Bayesian risk network, and relates to the field of water conservancy and hydropower engineering. The advantages in dealing with common cause failure problems solve the shortcomings of the traditional "three trees" (fault tree, event tree, and decision tree) in risk analysis of hydropower projects. Based on the Bayesian risk network model of cascade hydropower stations, an identification method for key risk factors and key paths of risk transfer is proposed, which provides theoretical and methodological support for applying the Bayesian risk network method of cascade hydropower stations to risk identification and prevention and control. The method is simple and clear, and has strong operability. It has an important application prospect in the risk identification and prevention and control of cascade hydropower projects and civil engineering similar system engineering using Bayesian networks.

Description

technical field [0001] The invention relates to a Bayesian risk network-based identification method for key risk factors and risk transfer key paths of cascade hydropower stations used in risk analysis, assessment, and control in the field of water conservancy and hydropower engineering. Background technique [0002] Cascade hydropower station projects, especially large-scale and giant projects, have the characteristics of large investment, long cycle, complex operating environment, and many influencing factors. It is a highly comprehensive system engineering. Affected by objective uncertain factors such as natural conditions (geology, hydrology, climate, etc.), construction conditions (environment, traffic, rolling, etc.) and subjective uncertain factors in design, construction and procurement, hydropower project construction and During the operation process, new problems and challenges are constantly encountered, and quality defects or hidden dangers may appear in all stag...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/06
CPCG06Q10/0635G06Q50/06
Inventor 张元泽刘浩吾陈群王仁坤李永红
Owner SICHUAN UNIV
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