Method and system for determining gas diffusion range

Abstract

The invention discloses a method and a system for determining a gas diffusion range. A gas outflow volume and a Gaussian puff multistage dynamic diffusion integral algorithm are adopted, the synthetic data analysis of conventional physicochemical multiparameters which are obtained through a traditional manual, database or experiment and are associated with natural gas pipeline leakage is used for determining a natural gas puff diffusion range, the problem that the natural gas leakage diffusion range can not be accurately predicted under the state of incomplete data is solved, the emergency control capability of a nation for coping with sudden accidents can be improved, and the method and the system have an important meaning on effectively avoiding heavy economic losses and personal casualties.

Description

technical field [0001] The present application relates to the field of municipal technology, in particular to a method and system for determining the gas diffusion range. Background technique [0002] For natural gas pipeline leakage, understanding and mastering the relationship between various relevant physical and chemical parameter data and natural gas diffusion range is of great significance for strengthening pipeline maintenance management, preventing leakage accidents, and accurately predicting the leakage range after accidents. [0003] However, it is difficult to find relevant parameters and natural gas leakage range prediction models from the existing literature, resulting in a severe lack of relevant parameter data after natural gas pipeline leakage occurs, and it is impossible to accurately predict the specific diffusion range of combustible gas after leakage. [0004] Natural gas pipeline leakage is a macroscopic, large-scale, and large-area event. Historical pip...

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Problems solved by technology

[0006] The embodiment of the present invention provides a method and system for determining the gas diffusion range, which is used to solve the problem that the research on existing prediction methods is not comprehensive enough, the model prediction stage is not comprehensive, and the analysis parameters are too few

Existing theoretical prediction methods are subject to relatively large limitations in practical engineering applications

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