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Method for determining piping penetration coefficient based on random start

A technology of permeability coefficient and determination method, which is applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., and can solve problems such as difficult to determine the number law of starting particles, and difficult to determine the number law

Active Publication Date: 2015-04-29
HOHAI UNIV
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Problems solved by technology

Even if it is known that the hydraulic critical condition of piping is in the starting state according to the previous judgment, it is difficult to determine the law of the number of starting particles because it is impossible to know the instantaneous velocity, diameter of starting particles, and their position and contact relationship at that time, that is, That is to say, if only the average permeation flow rate, the average particle size and the average position relationship of the particles are known, the number law is difficult to determine

Method used

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  • Method for determining piping penetration coefficient based on random start
  • Method for determining piping penetration coefficient based on random start
  • Method for determining piping penetration coefficient based on random start

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Embodiment 1

[0041] Embodiment 1: In this embodiment, seepage calculation is carried out by taking a large embankment as an example.

[0042] The levee adopts a homogeneous embankment structure, which is made of homogeneous clay accumulation, and the permeability coefficient is 1×10 -8 m / s, the upper layer of embankment is clay covering layer, and the permeability coefficient is 1×10 -6 m / s, the lower layer is sand layer, and the permeability coefficient is 1.5×10 -4 m / s. The physical indexes of the sand layer are shown in Table 1, where C c and C u are the coefficient of curvature and coefficient of inhomogeneity of the particle grading curve, G s is the relative density of soil particles, n is the initial porosity, d 10 、d 30 and d 60 They are the diameters of soil particles corresponding to 10%, 30% and 60% of mass cumulative percentages smaller than a certain particle size. Particle grading and calculation partition see figure 1 and figure 2 , the results of hydraulic gradie...

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Abstract

The invention discloses a method for determining a piping penetration coefficient based on random start. The method for determining the penetration coefficient in the piping generation and development process is based on distribution densities or probability functions of a mean speed, a mean particles size of particles and a mean positional relation, based on parameters of mathematical expectation and the like, and based on combination of mechanical analysis. The method has significance for reasonably evaluating the dam safety, predicting an area where penetration damage possibly occurs and the form and reducing the losses caused by the penetration damage.

Description

technical field [0001] The invention belongs to the technical field of groundwater seepage calculation, and in particular relates to a method for determining a piping seepage coefficient based on random start. Background technique [0002] In the past research on piping, attention was often focused on the study of the average characteristic (that is, the deterministic law), and the randomness of piping occurrence was not paid enough attention to. A considerable number of theoretical workers still used pure mechanical methods according to the inevitable phenomenon. Methods to conduct research without analyzing its randomness often fail to explain some actual phenomena. The randomness of piping can be understood from the following two aspects: 1) the randomness of the start of movable particles; 2) the randomness of the spatial distribution of soil properties. [0003] The essence of piping is the process in which movable particles move and lose in pores under the drag of wat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00
Inventor 董海洲柴文可
Owner HOHAI UNIV
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