One-dimensional hydraulic model of combustion in obstacles

Introduction. The question of the influence of the configuration of the obstacled space on the dynamics of the emergency explosion development, in particular on the intensity of flame acceleration, has been studied for quite a long time. In many works by experimental and numerical methods combustion in obstacles at their various quantity, mutual location, geometrical forms and other parameters is considered. Nevertheless, in most cases, obstacles arranged in organized and periodical manner are considered. At the same time, explosions of gas clouds can occur in conditions where obstacles represented by building structures and technological equipment are arranged in an unorganized manner.

Objective. To simulate the combustion process with an array of randomly placed obstacles, taking into account the specific parameters of the confined space (the number of obstacles nx, their average size d, blocking ratio BO and volumetric clutter θ) using the developed hydraulic model of explosion development.

Research method. The problem of combustion in a pipe closed at one end with specified geometric parameters is solved. Expressions for calculating the parameters of a confined space are given, as well as the principle according to which these parameters are integrated into a hydraulic model.

Description of the physical model. The system of basic differential and algebraic equations of the developed model is presented.

Results and discussion. Functions of the flame speed (Xf)’ to the path traversed by flame Xf are obtained. The calculation was carried out for obstacles with a size d = 1–4 cm at different θ (0.1–0.25) and BO (0.09–0.37), which were adjusted by changing nx.

Conclusion. With the growth of d or nx, the flame in the obstacled space accelerates more strongly. The growth of BO, like θ, leads to an increasing of the gas flow rate in front of the flame and the effective combustion rate. And, consequently, to more intense flame acceleration. Obtained results are make it possible to verify the model using experimental data and improve it in the future.

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