CN115688615A - Method, device, equipment, medium and product for determining number density of pipeline bubbles - Google Patents
Method, device, equipment, medium and product for determining number density of pipeline bubbles Download PDFInfo
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Abstract
The embodiment of the invention provides a method, a device, equipment, a medium and a product for determining the number density of bubbles in a pipeline, wherein the method comprises the following steps: acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline; inputting the fluid mechanics parameters into a preset double-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline; determining the current migration speed of each bubble according to the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble; and determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm. The method provided by the embodiment of the invention can determine the current number density of the bubbles in the target pipeline, and provides a basis for subsequently solving the problem of gas phase migration resistance of the pipeline.
Description
Technical Field
The embodiment of the invention relates to the technical field of oil and gas pipelines, in particular to a method, a device, equipment, a medium and a product for determining the number density of bubbles in a pipeline.
Background
In the large-drop pipeline, because of large drop, a water head flows to a downhill section in an open channel flow mode after crossing a high point of a pipeline section, liquid flows are accumulated at a low point of the pipeline, and finally a liquid plug is formed, so that gas is accumulated in the downhill pipeline section, and a large number of gas accumulation sections are formed in the continuous large-drop pipeline water combined transportation operation.
At the moment, if a U-shaped pipe section consisting of a downhill section, a low point and an uphill section is set as a basic unit, as the production is put into operation, a liquid plug of the uphill section can continuously grow along with the growth of a liquid plug of the low point, so that a downhill gas accumulation section can be subjected to continuously increased backpressure, and when the backpressure exceeds a certain threshold value, the tail of the gas accumulation section starts to be broken into small bubbles and moves downstream.
Along with broken bubble is constantly accumulated, there can be the gas phase migration problem of being obstructed in the great pipeline section of discrepancy in elevation, leads to the pipeline flow to hang down, reduces the efficiency that the pipeline transported the resource. If the problem of bubble migration needs to be solved, the number density of bubbles in the pipeline needs to be determined firstly, and a mode for determining the number density of bubbles is lacked at present.
Disclosure of Invention
The invention provides a method, a device, equipment, a medium and a product for determining the number density of bubbles in a pipeline, which are used for solving the problem that the current method for determining the number density of bubbles is lacked.
The first aspect of the embodiments of the present invention provides a method for determining number density of bubbles in a pipeline, including:
acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline;
inputting the fluid mechanics parameters into a preset double-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline;
determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm;
and determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm.
Optionally, in the method described above, the preset bubble migration speed algorithm includes: a bubble buoyancy algorithm and a bubble drag force algorithm;
the determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm comprises:
determining the bubble diameter corresponding to each bubble according to the current actual volume of each bubble;
inputting the fluid mechanics parameter and the bubble diameter into the bubble buoyancy algorithm to output the buoyancy borne by the bubble;
inputting the fluid mechanics parameter, the bubble diameter, the current liquid phase flow rate and the current gas phase flow rate into the bubble drag force algorithm to output the liquid flow drag force applied to the bubble;
and determining the current migration speed of the bubbles according to the buoyancy force borne by the bubbles and the liquid flow dragging force borne by the bubbles.
Optionally, the determining, according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble, and the preset number density algorithm, the current number density of the bubble in the target pipeline according to the method includes:
determining a corresponding calculated volume according to the current actual volume of each bubble and a preset conversion algorithm;
determining bubble polymerization crushing related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and bubble migration related parameters;
and inputting the current migration speed of each bubble, the bubble polymerization and fragmentation related parameters and the bubble migration related parameters into a preset number density algorithm to determine the current number density of the bubbles in the target pipeline.
Optionally, in the method described above, the bubble aggregation and fragmentation related parameters include an aggregation distribution coefficient between any two bubbles, a fragmentation distribution coefficient between any two bubbles, a coalescence probability between any two bubbles, and a fragmentation probability of each bubble;
determining bubble polymerization breakage related parameters according to the diameters of the bubbles, the current migration speed, the calculated volume, the current actual volume and the bubble migration related parameters, wherein the bubble polymerization breakage related parameters comprise:
inputting the current actual volume and the calculated volume of each bubble into a preset aggregation distribution coefficient algorithm to determine an aggregation distribution coefficient between any two bubbles;
determining the coalescence probability between any two bubbles and the breaking probability of each bubble according to the diameter of each bubble, the current migration speed of each bubble, the bubble migration related parameters and a preset coalescence probability algorithm;
determining the sub-bubble size distribution coefficient of each bubble according to the breaking probability of each bubble and a preset distribution coefficient algorithm;
and determining the fragmentation distribution coefficient between any two bubbles according to the current actual volume of each bubble, the calculated volume, the sub-bubble size distribution coefficient and a preset fragmentation distribution coefficient algorithm.
Optionally, in the method described above, the bubble migration related parameter includes an aggregation calculation coefficient and a volume type total amount into which the bubble volume is divided;
the preset number density algorithm is as follows:
wherein the term N represents the current number density, u b Represents the current migration velocity of the bubbles, δ represents an aggregation calculation coefficient, η represents an aggregation distribution coefficient between any two bubbles, ζ represents a fragmentation distribution coefficient between any two bubbles, c represents an aggregation probability between any two bubbles, b represents a fragmentation probability of the bubbles, t represents time, i, j, and k represent different bubbles, respectively, and M represents a total amount of the volume type of the bubbles.
Optionally, the method, after determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble, and the preset number density algorithm, further includes:
acquiring the sectional area of a target pipeline;
determining the total cross-sectional area of the bubbles in the target area according to the diameter of each bubble in the target area and the number density of the corresponding bubble;
determining whether a quotient between the total bubble cross-sectional area and a cross-sectional area of the target conduit is greater than or equal to a preset threshold;
and if the quotient is determined to be greater than or equal to a preset threshold value, determining that the long air bag exists in the target area of the target pipeline.
A second aspect of the embodiments of the present invention provides a device for determining a number density of bubbles in a pipeline, including:
the acquisition module is used for acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline;
the output module is used for inputting the fluid mechanics parameters into a preset double-fluid model so as to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline;
the speed determining module is used for determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm;
and the number density determining module is used for determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm.
Optionally, in the apparatus as described above, the preset bubble migration speed algorithm includes: a bubble buoyancy algorithm and a bubble drag force algorithm;
the speed determination module is specifically configured to:
determining the bubble diameter corresponding to each bubble according to the current actual volume of each bubble; inputting the hydrodynamic parameters and the bubble diameter into the bubble buoyancy algorithm to output buoyancy borne by the bubbles; inputting the hydrodynamic parameter, the bubble diameter, the current liquid phase flow rate and the current gas phase flow rate into the bubble drag force algorithm to output the liquid flow drag force applied to the bubble; and determining the current migration speed of the bubbles according to the buoyancy force borne by the bubbles and the liquid flow dragging force borne by the bubbles.
Optionally, in the above apparatus, the number density determining module is specifically configured to:
determining a corresponding calculated volume according to the current actual volume of each bubble and a preset conversion algorithm; determining bubble polymerization crushing related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and bubble migration related parameters; and inputting the current migration speed of each bubble, the bubble aggregation and fragmentation related parameters and the bubble migration related parameters into a preset number density algorithm to determine the current number density of the bubbles in the target pipeline.
Optionally, in the apparatus as described above, the bubble aggregation and fragmentation related parameters include an aggregation distribution coefficient between any two bubbles, a fragmentation distribution coefficient between any two bubbles, a coalescence probability between any two bubbles, and a fragmentation probability of each bubble;
the number density determining module is specifically configured to, when determining the bubble aggregation breakage related parameter according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume, and the bubble migration related parameter:
inputting the current actual volume and the calculated volume of each bubble into a preset aggregation distribution coefficient algorithm to determine an aggregation distribution coefficient between any two bubbles; determining the coalescence probability between any two bubbles and the breakage probability of each bubble according to the diameter of each bubble, the current migration speed of each bubble, the bubble migration related parameters and a preset coalescence probability algorithm; determining the sub-bubble size distribution coefficient of each bubble according to the breaking probability of each bubble and a preset distribution coefficient algorithm; and determining the fragmentation distribution coefficient between any two bubbles according to the current actual volume of each bubble, the calculated volume, the sub-bubble size distribution coefficient and a preset fragmentation distribution coefficient algorithm.
Optionally, in the apparatus as described above, the bubble migration related parameter includes an aggregation calculation coefficient and a volume type total amount into which the bubble volume is divided;
the preset number density algorithm is as follows:
wherein the N term represents the current number density, u b Represents the current migration velocity of the bubbles, δ represents an aggregation calculation coefficient, η represents an aggregation distribution coefficient between any two bubbles, ζ represents a fragmentation distribution coefficient between any two bubbles, c represents a coalescence probability between any two bubbles, b represents a fragmentation probability of the bubbles, t represents time, i, j, and k represent different bubbles, respectively, and M represents the total amount of the volume type of the bubbles.
Optionally, the apparatus as described above, further comprising:
the long air bag determining module is used for acquiring the sectional area of a target pipeline; determining the total cross-sectional area of the bubbles in the target area according to the diameter of each bubble in the target area and the number density of the corresponding bubble; determining whether a quotient between the total bubble cross-sectional area and a cross-sectional area of the target conduit is greater than or equal to a preset threshold; and if the quotient is determined to be greater than or equal to a preset threshold value, determining that the long air bag exists in the target area of the target pipeline.
A third aspect of an embodiment of the present invention provides an electronic device, including: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the method for determining the number density of bubbles in the pipeline according to any one of the first aspect.
A fourth aspect of the embodiments of the present invention provides a computer-readable storage medium, where computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the method for determining a bubble number density of a pipeline according to any one of the first aspect is implemented.
A fifth aspect of the embodiments of the present invention provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method for determining the bubble number density of the pipeline according to any one of the first aspect is implemented.
The embodiment of the invention provides a method, a device, equipment, a medium and a product for determining the number density of bubbles in a pipeline, wherein the method comprises the following steps: acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline; inputting the fluid mechanics parameters into a preset double-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline; determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm; and determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm. The method for determining the number density of the bubbles in the pipeline, provided by the embodiment of the invention, adopts a double-fluid model to determine the current liquid phase flow rate and the current gas phase flow rate of fluid in a target pipeline, provides a basis for determining the migration speed of each bubble, and simultaneously determines the current migration speed of each bubble by integrating the current actual volume of each bubble, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm. The number density of the bubbles is relatively high in correlation with the migration speed and the volume of the bubbles, so that the current number density of the bubbles in the target pipeline can be determined according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm, and a basis is further provided for subsequently solving the problem that the gas phase migration of the pipeline is blocked.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a scene diagram of a method for determining the number density of bubbles in a pipeline, which can implement the embodiment of the present invention;
FIG. 2 is a schematic flowchart of a method for determining a bubble number density of a pipeline according to a first embodiment of the present invention;
FIG. 3 is a schematic flowchart of a method for determining the bubble number density of a pipeline according to a second embodiment of the present invention;
FIG. 4 is a schematic diagram of a long balloon of a pipeline according to a method for determining bubble number density of the pipeline according to a second embodiment of the present invention;
FIG. 5 is a schematic diagram of volume division in a method for determining the bubble number density of a pipeline according to a second embodiment of the present invention;
FIG. 6 is a schematic diagram illustrating the force exerted on bubbles in the method for determining the number and density of bubbles in a pipeline according to the second embodiment of the present invention;
FIG. 7 is a schematic structural diagram of a device for determining the bubble number density in a pipeline according to a third embodiment of the present invention;
FIG. 8 is a schematic structural diagram of a device for determining the bubble number density of a pipeline according to a fourth embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.
With the above figures, certain embodiments of the invention have been illustrated and described in more detail below. The drawings and the description are not intended to limit the scope of the inventive concept in any way, but rather to illustrate it by those skilled in the art with reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The technical means of the present invention will be described in detail with reference to specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
For a clear understanding of the technical solutions of the present application, a detailed description of the prior art solutions is first provided. At present, in the process of putting a large-fall liquid pipeline into production, a plurality of gas accumulation sections are formed at each downhill section, and the gas accumulation sections are broken into small bubbles in the process of putting the liquid pipeline into production and are transported to the downstream. In the migration process, the bubbles collide with each other under the action of turbulence, the collision probability is high when the number density is high, and the collision probability is low when the number density is low. And upon collision, some of the bubbles converge and come together to form larger bubbles. Some of the bubbles will continue to break up into smaller sized bubbles due to the turbulent flow of the liquid phase. Therefore, after bubbles of different sizes break up from the gas accumulation section, their downstream migration is accompanied by different degrees of coalescence and fragmentation. Along with broken bubble is constantly accumulated, there can be the gas phase migration problem of being obstructed in the great pipeline section of discrepancy in elevation, leads to the pipeline flow to hang down, reduces the efficiency that the pipeline transported the resource. If the problem of bubble migration needs to be solved, the number density of bubbles in the pipeline needs to be determined firstly, and a mode for determining the number density of bubbles is lacked at present.
Therefore, in order to solve the problem of the prior art that the number density of the bubbles is not determined, the inventor finds in research that in the process of production, the bubble size distribution is wide, and the bubble size distribution is large, and the calculation amount is huge if the coalescence and the breakage of the bubbles with any size are determined. A number density algorithm may thus be constructed in conjunction with the population group balance model to determine the number density of the target conduit bubble. Specifically, the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline are obtained. And determining the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline by adopting a double-fluid model, providing a basis for determining the migration speed of each bubble, and meanwhile, determining the current migration speed of each bubble by integrating the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble. The number density of the bubbles is relatively high in correlation with the migration speed and the volume of the bubbles, so that the current number density of the bubbles in the target pipeline can be determined according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble and a preset number density algorithm, and a basis is provided for solving the problem of gas phase migration blockage of the pipeline subsequently.
The inventor provides the technical scheme of the application based on the creative discovery.
An application scenario of the method for determining the number and density of bubbles in a pipeline provided by the embodiment of the invention is described below. As shown in fig. 1, 1 is a first electronic device, and 2 is a second electronic device. The network architecture of the application scenario corresponding to the method for determining the number density of the pipeline bubbles provided by the embodiment of the invention comprises the following steps: a first electronic device 1 and a second electronic device 2. The second electronic device 2 stores the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline. When the number density of bubbles in the pipeline needs to be determined, the first electronic device 1 obtains the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline from the second electronic device 2. Then, the first electronic device 1 obtains the current actual volume, the fluid mechanics parameter and the related parameter of bubble migration of each bubble in the target pipeline, meanwhile, the first electronic device 1 inputs the fluid mechanics parameter into a preset dual-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline, and then the current migration speed of each bubble is determined according to the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble. And finally, the first electronic equipment 1 determines the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm. And after the current number density of the bubbles in the target pipeline is determined, the current number density can be sent to other equipment to perform corresponding processing on the target pipeline, so that the problem of blocked gas phase migration of the pipeline is solved.
The embodiments of the present invention will be described with reference to the drawings.
Fig. 2 is a schematic flowchart of a method for determining a number density of bubbles in a pipeline according to a first embodiment of the present invention, and as shown in fig. 2, in this embodiment, an execution subject of the embodiment of the present invention is a device for determining a number density of bubbles in a pipeline, where the device for determining a number density of bubbles in a pipeline may be integrated in an electronic device. The method for determining the number and density of the bubbles in the pipeline provided by the embodiment comprises the following steps:
step S101, obtaining the current actual volume, the fluid mechanics parameter and the air bubble migration related parameter of each air bubble in the target pipeline.
In this embodiment, the obtaining manner may be obtained from a database in which the current actual volume, the fluid mechanics parameter, and the bubble migration related parameter of each bubble in the target pipeline are stored, or may be obtained from other acquisition devices, which is not limited in this embodiment.
In order to improve the calculation efficiency, the actual volume that the air bubbles may reach under different working conditions may be divided into M volume types, that is, into M volume ranges, and when the current actual volume of each air bubble belongs to which range, the calculation may be performed according to the volume of the range. For example, if the current actual volume is 0.1 cubic millimeter and belongs to the volume type of 0.05-0.1 cubic millimeter, the calculation is performed according to the volume type range.
Because the bubbles change with time, for example, the volume and the speed change with time, the method for determining the number density of bubbles in the pipeline in this embodiment obtains the current actual volume of each bubble at the current time, thereby providing a basis for subsequently determining the current number density of the target pipeline.
The fluid mechanics parameters may include gravitational acceleration, gas phase fraction, liquid phase fraction, gas phase density, liquid phase density, friction, pressure, angular magnitude of force, and other fluid mechanics related parameters.
The bubble migration related parameters may include the minimum size of the turbulence that can cause the bubble to break up into vortices, the probability density of the bubble breaking after encountering a vortex of a certain size, the weber number, the aggregation calculation coefficient, and the like.
Step S102, inputting the fluid mechanics parameters into a preset two-fluid model so as to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline.
The preset two-fluid model is as follows:
wherein k may represent a gas phase or a liquid phase, when k represents a liquid phase, the two-fluid model is a liquid-phase two-fluid model, and when k represents a gas phase, the two-fluid model is a gas-phase two-fluid model, α k Represents the gas phase orLiquid phase fraction, ρ k Represents the density of the gas or liquid phase, u k Representing the current gas or liquid phase flow rate, Γ k Representing the gas or liquid phase friction term, P representing the pressure, M k Representing the mass of each phase, t representing time, x representing distance, θ representing the angle of the fluid to the horizontal, and g representing the acceleration of gravity.
And step S103, determining the current migration speed of each bubble according to the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble.
In this embodiment, the current migration velocity of each bubble is greatly related to the fluid state of the target pipeline, such as the current liquid phase flow rate and the current gas phase flow rate. Therefore, the current migration speed of each bubble can be determined through the current actual volume, the fluid mechanical parameters, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble.
And step S104, determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm.
In this embodiment, since the number density of the bubbles has a larger relationship with the current actual volume of each bubble and the bubble migration, the current number density of the bubbles in the target pipeline may be determined according to the current actual volume of each bubble, a parameter related to the bubble migration, the current migration speed of each bubble, and a preset number density algorithm.
The embodiment of the invention provides a method for determining the number density of bubbles in a pipeline, which comprises the following steps: and acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline. And inputting the fluid mechanics parameters into a preset double-fluid model so as to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline. And determining the current migration speed of each bubble according to the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble. And determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm. The method for determining the number density of the bubbles in the pipeline, provided by the embodiment of the invention, adopts a double-fluid model to determine the current liquid phase flow rate and the current gas phase flow rate of fluid in a target pipeline, provides a basis for determining the migration speed of each bubble, and simultaneously determines the current migration speed of each bubble by integrating the current actual volume, the fluid mechanics parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm of each bubble. The number density of the bubbles is relatively high in correlation with the migration speed and the volume of the bubbles, so that the current number density of the bubbles in the target pipeline can be determined according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm, and a basis is further provided for subsequently solving the problem that the gas phase migration of the pipeline is blocked.
Fig. 3 is a schematic flow chart of a method for determining the number density of bubbles in a pipeline according to a second embodiment of the present invention, and as shown in fig. 3, the method for determining the number density of bubbles in a pipeline according to the present embodiment is further refined in each step based on the method for determining the number density of bubbles in a pipeline according to the previous embodiment of the present invention. The method for determining the bubble number density of the pipeline provided by the embodiment comprises the following steps.
Step S201, obtaining the current actual volume, the fluid mechanics parameter, and the bubble migration related parameter of each bubble in the target pipeline.
In this embodiment, the implementation manner of step 201 is similar to that of step 101 in the previous embodiment of the present invention, and is not described in detail here.
Step S202, inputting the fluid mechanics parameters into a preset two-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline.
In this embodiment, the implementation manner of step 202 is similar to that of step 102 in the previous embodiment of the present invention, and is not described herein again.
It should be noted that the preset bubble migration velocity algorithm includes: a bubble buoyancy algorithm and a bubble drag force algorithm.
Step S203, determining the bubble diameter corresponding to each bubble according to the current actual volume of each bubble.
In this embodiment, since the shape of the bubble is variable, the bubble is defaulted to a sphere for convenience of calculation. The bubble diameter corresponding to each bubble can be determined according to the current actual volume of each bubble through a volume formula of the sphere.
Step S204, inputting the fluid mechanics parameter and the bubble diameter into a bubble buoyancy algorithm to output the buoyancy borne by the bubble.
In this embodiment, the fluid mechanics parameters include gas phase density, liquid phase density, and gravitational acceleration.
In this embodiment, the bubble buoyancy algorithm is:
wherein, F b o u Representing the buoyancy to which the bubble is subjected, p g Represents the density of the gas phase, p l Represents the density of the liquid phase, d b Represents the bubble diameter and g represents the acceleration of gravity.
Step S205, inputting the fluid mechanics parameter, the bubble diameter, the current liquid phase flow rate and the current gas phase flow rate into a bubble dragging force algorithm to output the liquid flow dragging force applied to the bubble.
In this embodiment, the fluid mechanics parameter may include a liquid phase density and a drag coefficient.
In this embodiment, the bubble drag force algorithm is:
wherein, F Drag The drag force of the liquid stream on the bubble, ρ l Represents the density of the liquid phase, d b Represents the diameter of the bubble, C D Representing the drag coefficient, u l Represents the current liquid phase flow rate, u g Representing the current gas phase flow rate.
And step S206, determining the current migration speed of the bubbles according to the buoyancy force borne by the bubbles and the liquid flow dragging force borne by the bubbles.
In this embodiment, according to newton's second law, the current migration velocity of the bubble can be determined according to the buoyancy force applied to the bubble and the liquid flow drag force applied to the bubble, that is, the force applied to the bubble is equal to the mass of the bubble multiplied by the acceleration of the bubble.
The total force to which the bubble is subjected is:
F b ＝(m b g-F buo )cosθ+F Drag
wherein m is b The bubble mass is theta, the included angle between the horizontal direction and the pipeline direction is theta, and g is the gravity acceleration.
Step S207, determining a corresponding calculated volume according to the current actual volume of each bubble and a preset conversion algorithm.
In this embodiment, since the volume of the bubble is relatively complex, for the convenience of calculation, the volume of the bubble is divided into M volume types (v) 1 ，v 2 ，…v M ) Namely, a volume range is defined, the volume of the bubbles which possibly appear under different working conditions is basically contained, and on the basis, the calculated volume is increased for better determining the current number density of the bubbles.
The conversion relation between the calculated volume and the actual volume of the bubble is as follows:
g 1 +g 2 ＝2v 2
the number of volumes calculated is M-1, i.e. (g) 1 ，g 2 ，…g M-1 )。
And step S208, determining the bubble polymerization and fragmentation related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and the bubble migration related parameters.
Optionally, in this embodiment, the bubble aggregation and fragmentation related parameters include an aggregation distribution coefficient between any two bubbles, a fragmentation distribution coefficient between any two bubbles, a coalescence probability between any two bubbles, and a fragmentation probability of each bubble.
Determining bubble polymerization and fragmentation related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and the bubble migration related parameters, wherein the bubble polymerization and fragmentation related parameters comprise:
and inputting the current actual volume and the calculated volume of each bubble into a preset aggregation distribution coefficient algorithm to determine an aggregation distribution coefficient between any two bubbles.
And determining the coalescence probability between any two bubbles and the breakage probability of each bubble according to the diameter of each bubble, the current migration speed of each bubble, the bubble migration related parameters and a preset coalescence probability algorithm.
And determining the sub-bubble size distribution coefficient of each bubble according to the breaking probability of each bubble and a preset distribution coefficient algorithm.
And determining the fragmentation distribution coefficient between any two bubbles according to the current actual volume, the calculated volume, the size distribution coefficient of the sub-bubbles and a preset fragmentation distribution coefficient algorithm of each bubble.
In this embodiment, the preset aggregate distribution coefficient algorithm is as follows:
wherein eta is i ， jk Represents the aggregate distribution coefficient between the ith bubble and the jth or kth bubble, and v represents the current actual volume of the ith bubble. g i 、g i-1 、g i+1 Respectively represent the ith, ith-1 and ith +1 calculated volumes.
In order to improve the efficiency of the operation, the volume of each bubble can be divided into each volume type during calculation on the basis of dividing the actual volume into M and dividing the calculated volume into M-1. I.e. v represents the volume range to which the current actual volume of the i-th bubble belongs, g i 、g i-1 、g i+1 Respectively represent the volume ranges of the ith, ith-1 and ith +1 calculated volumes. The following same principles relating to the actual volume, calculated volume and diameter of the bubbles will not be described in detail.
The preset clustering probability algorithm is as follows:
c i,j ＝c(d i ,d j )＝ω(d i ,d j )P(d i ,d j )
wherein, ω (d) i ,d j ) Representing two diameters d i ,d j Probability of collision of bubbles, P (d) i ,d j ) Representing two diameters d i ,d j Probability of combination after bubble collision, c i ， j Representing the probability of coalescence between the ith bubble and the jth bubble.
At the same time, the user can select the required time,
wherein xi is ij Representing two diameters d i ,d j Diameter ratio, ξ, of the bubbles ij ＝d i /d j ，We ij Representing the Weber number of the bubble,. Psi.is typically 1, and. Gamma.is typically 0.5,. Rho g Represents the density of the gas phase, p l Representing the density of the liquid phase.
The preset distribution coefficient algorithm is as follows:
wherein, β (f) v | d) represents a diameter of d and a fragmentation fraction of f v B (f) is the size distribution coefficient of the sub-bubbles of the bubble v | d) represents a diameter of d and a fragmentation fraction of f v The probability of breakage of the bubbles.
The preset crushing distribution coefficient algorithm is as follows:
wherein β represents a size distribution coefficient of bubbles, g i 、g i-1 、g i+1 Respectively represent the ith, ith-1 and ith +1 th calculated volumes, v represents the actual volume of the bubble and k represents the calculated volume of the bubble different from i.
Step S209, inputting the current migration speed of each bubble, the bubble aggregation and fragmentation related parameters, and the bubble migration related parameters into a preset number density algorithm to determine the current number density of the bubbles in the target pipeline.
Optionally, in this embodiment, the bubble migration related parameter includes an aggregation calculation coefficient and a volume type total amount into which the bubble volume is divided.
The preset number density algorithm is as follows:
wherein the N term represents the current number density, u b Represents the current migration velocity of the bubbles, δ represents an aggregation calculation coefficient, η represents an aggregation distribution coefficient between any two bubbles, ζ represents a fragmentation distribution coefficient between any two bubbles, c represents an aggregation probability between any two bubbles, b represents a fragmentation probability of the bubbles, t represents time, i, j, and k represent different bubbles, respectively, and M represents a total amount of the volume type of the bubbles.
The volume type total may be how many volume sizes the bubble is present, i.e., how many volume type total.
Similarly, in order to further improve the operation efficiency, the actual volume may be divided into M, and the volume of each bubble may be divided into each volume type during calculation on the basis of dividing the calculated volume into M-1, which is not described herein again.
Optionally, in this embodiment, after determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble, and a preset number density algorithm, the method further includes:
a cross-sectional area of a target region of a target conduit is obtained.
And determining the total cross-sectional area of the bubbles in the target area according to the diameter of each bubble in the target area and the number density of the corresponding bubble.
It is determined whether a quotient between the total cross-sectional area of the bubble and the cross-sectional area of the target conduit is greater than or equal to a preset threshold.
And if the quotient is larger than or equal to the preset threshold value, determining that the long air bag exists in the target area of the target pipeline.
In this embodiment, the long air cells are formed by the coalescence of the bubbles due to their high number density in a certain space, and thus, the presence or absence of the long air cells can be determined according to the number density of the target pipe. Meanwhile, the long air bags in the different areas of the target pipeline can be determined according to the distribution condition of the air bubbles in the different areas, so that the positions of the long air bags are determined, and a basis is provided for subsequent treatment matters aiming at the long air bags. The long air bag is generated by the migration of bubbles in the pneumatosis segment, and theta is the included angle between the pipeline and the horizontal plane, as shown in figure 4. The total cross-sectional area of the bubbles of the target pipeline can be obtained by calculating the corresponding cross-sectional area of the diameter and the corresponding number density of each bubble, and then accumulating the cross-sectional area of each bubble to obtain the total cross-sectional area of the bubbles of the target pipeline.
In order to more conveniently determine the total cross-sectional area of the bubbles of the target pipeline, the total cross-sectional area of the bubbles of the target pipeline can be obtained by performing accumulation calculation on the bubbles according to the attributive volume type range, the accumulation of the cross-sectional area of the actual volume of each bubble is not needed, and the calculation amount is reduced. Meanwhile, the preset threshold value can be 0.3, and then the algorithm for judging whether the long airbag exists is as follows:
where M represents the total number of bubble volume types, i represents the ith calculated volume type, d i Represents the diameter of the i-volume type bubble, N (i, t) represents the number density of the i-th volume type bubble, and D represents the cross-sectional area of the target conduit.
Meanwhile, in order to better understand the method for determining the bubble number density of the pipeline according to the embodiment of the present invention, a more detailed determination process will be illustrated below with reference to the accompanying drawings. During the production process of the large-fall liquid pipeline, a plurality of gas accumulation sections are formed on each downhill section, and the gas accumulation sections are broken into small bubbles and are transported downstream during the production process. During the production process, bubble breakage and coalescence all occur at any moment, the sizes of the bubbles are also widely distributed, and the calculated amount becomes huge if the coalescence and breakage of the bubbles with any size are determined. In addition, the bubbles are subjected to various forces during the migration of the downward slope section, and the migration characteristics of the bubbles are complicated. Therefore, to investigate this problem clearly, the embodiment of the present invention is intended to start with four steps: (1) A Population Balance Model (called Population Balance Model in English) was introduced to describe coalescence and fragmentation of bubbles. (2) On the basis, an Euler-Lagrange method is introduced to describe the migration of the bubbles with different scales in the downhill section. And (3) dispersing the equation, and giving a solving method. (4) The conditions for the formation of long air cells due to bubble aggregation are listed.
(1) Population balance model: coalescence and fragmentation between bubbles
A population balance model for bubbles solves the problem of infinite possible bubble sizes by classifying bubbles into M volume types (v) 1 ,v 2 ,…v M ) I.e. framing a volume range to substantially contain the volume of bubbles that may occur under different conditions (v) 1 ～v M ) On the basis of the calculated volume types M-1 (g) in the population group balance model are obtained 1 ,g 2 ,…g M-1 ) This is done to avoid an overrun condition during the calculation, e.g. volume v M The bubble of (2) is combined with other bubbles to form a larger bubble beyond the boundary, and the calculation cannot be continued. A schematic diagram of actual volume type versus calculated volume type is shown in fig. 5.
In fig. 5, the conversion relationship between the calculated volume type and the actual volume type is: g 1 +g 2 ＝2v 2 And so on until gM-1. It can also be seen that a volume is v and is between v 1 ,v 2 In the calculation, the bubbles are distributed to g according to a certain proportion 1 ,g 2 The volume range of the mixture is that,and then corresponding calculation is carried out. Thus, bubbles of different sizes can be distributed to g in a certain ratio 1 ～g M-1 Then, the formula of bubble coalescence and fragmentation can be adjusted to calculate the bubble particle size distribution at different times and positions, and the population group balance model of the bubbles is as follows:
wherein the first term on the left of the equation is the transient term and the second term is the conservation of mass term. The first term on the right of the equation is the positive source term (C) due to bubble coalescence B ) The second term is the negative source term (C) of bubble aggregation D ) The third term is a positive source term (B) due to bubble collapse B ) The fourth term is the negative source term (B) of bubble collapse D ). The definition of the terms positive and negative origin derives from the concept of "birth" and "death", and if two small bubbles are merged into one large bubble, it means that two small bubbles are "dead" and one large bubble is "birth". On the contrary, if one large bubble is broken into two small bubbles, it can be regarded that one large bubble is "dead" and two small bubbles are "born". Over time, the air bubbles interact with each other and the population evolves differently between different groups, as in a society, due to birth rates and mortality of the population, and thus presents the population at different age stages at different times. The population balance model of the bubble is to introduce a positive source term (birth rate) and a negative source term (death rate) to describe the number density distribution of the bubble presented at different moments.
According to the embodiment of the invention, the population group balance model of the bubbles is solved in a discrete form, and the following can be obtained after the dispersion:
wherein, N represents the current number density, u b Representing the current migration velocity of the bubble, and δ representingAn aggregation calculation coefficient, η represents an aggregation distribution coefficient between any two bubbles, ζ represents a fragmentation distribution coefficient between any two bubbles, c represents an aggregation probability between any two bubbles, b represents a fragmentation probability of bubbles, t represents time, i, j, and k represent different bubbles, respectively, and M represents a total volume type amount into which the bubble volume is divided. And the aggregate distribution coefficient η between any two bubbles:
wherein eta is i ， jk Represents the aggregate distribution coefficient between the ith bubble and the jth bubble or kth bubble, and v represents the current actual volume of the ith bubble. g is a radical of formula i 、g i-1 、g i+1 Respectively represent the ith, ith-1 and ith +1 calculated volumes.
Crushing distribution coefficient ζ:
wherein β represents a size distribution coefficient of bubbles, g i 、g i-1 、g i+1 Respectively represent the ith, ith-1 and ith +1 calculated volumes, v represents the actual volume of the bubble and k represents the calculated volume of the bubble different from i.
After the two distribution coefficients are obtained, the convergence probability c, the fragmentation probability b and the sub-bubble size distribution coefficient beta can be obtained for solving.
For the solution of the parameters, a premise needs to be explained, the factors of bubble collision and fragmentation are many, and in the process of large-drop water intermodal transportation, after bubbles are stripped from an air accumulation section, the bubbles are transported in a downhill section, and the main factors of coalescence and fragmentation are that the bubbles are in a liquid phase turbulent environment, and due to the existence of vortexes in the liquid phase turbulence, the bubble collision and the bubble tearing (namely, fragmentation) are caused, so that the bubble coalescence probability c and the fragmentation probability b caused by the turbulent vortexes need to be solved.
First, the coalescence probability c consists of two parts: probability of collision and probability of post-collision coalescence:
c i,j ＝c(d i ,d j )＝ω(d i ,d j )P(d i ,d j )
wherein:
wherein:
ω(d i ,d j ) Two diameters are each d i ,d j The collision probability of the bubbles.
P(di,d j ) Two diameters each being d i ,d j Probability of combination after bubble collision.
ξ ij -ratio of diameters of two bubbles, ξ ij ＝d i /d j 。
We ij Weber number, we ij ＝ρ l d i (u i 2 +u j 2 ) 0.5 /σ。
σ -surface tension of water, N/m.
Psi-coefficient, take 1.
Gamma-coefficient, 0.5.
ρ g Represents the density of the gas phase, p l Representing the density of the liquid phase.
After the probability of bubble coalescence is obtained, the probability of bubble breakage is further obtained, the bubble breakage is caused by that bubbles are torn into two bubbles under the action of turbulent vortex, so that the breakage probability algorithm is based on the interaction mechanism of the turbulent vortex and the bubbles:
wherein:
where λ min is the smallest size in the turbulent flow that can cause bubble breakup vortices. Pb (fv | d) is a bubble having a diameter d and a fragmentation fraction fv, and having a fragmentation probability density, α, after encountering a vortex of size λ g Is the gas phase fraction,. Epsilon.is the bubble migration related parameter, and d is the diameter of the bubble. After this term is obtained, the size distribution coefficient β (fv | d) of the sub-bubble is:
wherein, β (f) v D) represents a diameter of d and a fraction of fragmentation of f v B (f) is the size distribution coefficient of the sub-bubbles of the bubble v | d) represents a diameter of d and a fragmentation fraction of f v The probability of breakage of the bubbles.
(2) Euler-Lagrange method: migration of bubbles of different sizes in downhill section
In the bubble migration of the downhill section, the bubble migration is carried out at a liquid plug section after the gas accumulation section is broken, and if the migration of bubbles needs to be researched, the hydraulic calculation of the liquid flow of the downhill section in the large-fall pipeline needs to be completed at first. The embodiment of the invention introduces a one-dimensional double-fluid model to complete hydraulic calculation:
the upper formula of the two-fluid model is a continuity equation, and the lower formula is a momentum equation. Wherein: wherein k can represent a gas phase or a liquid phase, when k represents a liquid phase, the two-fluid model is a liquid-phase two-fluid model, and when k represents a gas phase, the two-fluid model is a gas-phase two-fluid model, alpha k In gas or liquid phase fraction, p k Is gas or liquid density, u k Of gas or liquid phase flow rate, gamma k Is a gas or liquid phase friction term, P is pressure, M k Represents the phase mass, t represents time, and x represents distance.
It should be noted that the two-fluid model is described for the euler-euler method. The two-fluid model is introduced to carry out hydraulic calculation, and the liquid phase flow velocity u required in the calculation of bubble migration can be given L And (5) waiting for the parameters of the basic flow field, and laying a foundation for the subsequent bubble migration calculation.
After listing the hydro-calculation algorithm, it is necessary to list the algorithm describing the bubble migration:
the algorithm for describing the bubble migration has the formula of bubble number density algorithm, and is also the bubble continuity algorithm listed by the Euler method. The following is the bubble momentum algorithm listed with the lagrange method. Therefore, the algorithm combines the Eulerian method and the Lagrange method to describe the migration characteristic of the bubbles, so that the method is called as the Eulerian-Lagrange method. Wherein, in the bubble momentum algorithm, fb is the resultant force of the bubbles in the flow direction, m b Corresponding bubble mass. And the resultant force experienced by the bubbles is shown in figure 6.
Wherein Fbou is the buoyancy force experienced by the bubble, FDrag is the liquid flow drag force experienced by the bubble, and m b g is the gravity borne by the bubbles, and theta is the included angle between the target pipeline and the horizontal plane. Therefore, the method comprises the following steps:
F b ＝(m b g-F buo )cosθ+F Drag
wherein:
wherein:
wherein, mu L Representing the dynamic viscosity of the liquid phase. C D Representing drag coefficient, re b Representing the Reynolds number, ρ, of the bubble l Represents the density of the liquid phase, d b Represents the diameter of the bubble, u l Represents the current liquid phase flow rate, u g Representing the current gas phase flow rate.
(3) Method for discretizing and solving algorithm in model
After the above algorithm enumeration is completed, discrete solution of the algorithm is required next.
In order to solve the control algorithm, the staggered grids are adopted for dispersing the pipelines, namely parameters such as storage pressure and phase content rate of the main grid, and only speed parameters are stored on the auxiliary grid. And then the control algorithm is dispersed by adopting a first-order windward format. For the continuity algorithm and the momentum algorithm in the two-fluid model, the discrete algorithm can be expressed as:
for the Euler-Lagrange method for describing bubble migration, in order to ensure the consistency of solution, a first-order windward format is also adopted to be dispersed in the same set of staggered grids, and the dispersion is as follows:
after the calculation of the algorithm is completed, the migration speed and the number density of bubbles with various volumes in the flow field can be calculated.
(4) Formation of long air bags
After completing (1) - (3), the method has calculated hydraulic parameters of the flow field, velocity of each volume of bubbles, and updated number density taking into account coalescence and fragmentation among bubbles. Thus, the velocity and density of each bubble group can be calculated in real time in the pipeline at each time step and at each distance step. Then, if it is necessary to describe the clear re-aggregation of bubbles into long cells, the critical conditions for the transition of bubbles into long cells are listed.
If the long air sac continues to swallow the air bubble, the long air sac will grow into a long taylor bubble, namely an air accumulation section. Therefore, a long balloon belongs substantially to a taylor bulb, and may be defined as a shorter taylor bulb. The long air bags are formed by the mutual combination of bubbles due to the high number density of the bubbles in a certain space, and the characteristic of the conversion from bubble flow to slug flow is also met.
In a space, the bubbles will collide and coalesce randomly, forming a few slightly larger individual bubbles, and as the gas flow increases, at these lower liquid flow rates the bubble density increases and reaches a critical point where the dispersed bubbles become so tightly packed together that many collisions occur and the velocity of the coalescence into larger bubbles increases dramatically, resulting in a transition to slug flow. It has been found through a large number of experiments that the gas phase content in the bubble flow hardly exceeds 0.35. When the gas content is 0.25 to 0.3, the bubble flow is changed to slug flow. Considering the actual situation, we take 0.3 as the transition boundary point.
Accordingly, the present examples set forth transition conditions for long balloon formation:
where M represents the total number of bubble volume types, i represents the ith calculated volume type, d i Represents the diameter of the i-volume type bubble, N (i, t) represents the number density of the i-th volume type bubble, and D represents the cross-sectional area of the target conduit.
The gas phase content of the cross section is obtained by adding the cross sectional areas of the bubbles of the respective volume types and dividing the sum by the cross sectional area of the pipe, and if the value is 0.3 or more, it is considered that the long air cell forming condition is satisfied here.
Fig. 7 is a schematic structural diagram of a device for determining a number density of bubbles in a pipeline according to a third embodiment of the present invention, as shown in fig. 7, in this embodiment, the device 300 for determining a number density of bubbles in a pipeline includes:
the obtaining module 301 is configured to obtain a current actual volume, a fluid mechanics parameter, and a bubble migration related parameter of each bubble in the target pipeline.
The output module 302 is configured to input the fluid mechanics parameter into a preset two-fluid model to output a current liquid phase flow rate and a current gas phase flow rate of the fluid in the target pipeline.
And the speed determining module 303 is configured to determine the current migration speed of each bubble according to the current actual volume, the hydrodynamic parameter, the current liquid-phase flow rate, the current gas-phase flow rate, and a preset bubble migration speed algorithm of each bubble.
The number density determining module 304 is configured to determine the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble, and a preset number density algorithm.
The device for determining the number and density of bubbles in a pipeline provided in this embodiment may implement the technical solution of the method embodiment shown in fig. 2, and the implementation principle and technical effect thereof are similar to those of the method embodiment shown in fig. 2, and are not described in detail herein.
Meanwhile, fig. 8 is a schematic structural diagram of a device for determining the number density of bubbles in a pipeline according to a fourth embodiment of the present invention, and as shown in fig. 8, the device for determining the number density of bubbles in a pipeline according to the present invention further refines the device 400 for determining the number density of bubbles in a pipeline on the basis of the device for determining the number density of bubbles in a pipeline according to the previous embodiment.
Optionally, in this embodiment, the preset bubble migration speed algorithm includes: a bubble buoyancy algorithm and a bubble drag force algorithm.
The speed determination module 303 is specifically configured to:
and determining the bubble diameter corresponding to each bubble according to the current actual volume of each bubble. And inputting the fluid mechanics parameter and the bubble diameter into a bubble buoyancy algorithm to output the buoyancy borne by the bubbles. And inputting the fluid mechanics parameter, the bubble diameter, the current liquid phase flow rate and the current gas phase flow rate into a bubble dragging force algorithm so as to output the liquid flow dragging force applied to the bubble. And determining the current migration speed of the bubbles according to the buoyancy force borne by the bubbles and the liquid flow dragging force borne by the bubbles.
Optionally, in this embodiment, the number density determining module 304 is specifically configured to:
and determining the corresponding calculated volume according to the current actual volume of each bubble and a preset conversion algorithm. And determining the bubble polymerization crushing related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and the bubble migration related parameters. And inputting the current migration speed of each bubble, the bubble aggregation and fragmentation related parameters and the bubble migration related parameters into a preset number density algorithm to determine the current number density of the bubbles in the target pipeline.
Optionally, in this embodiment, the bubble aggregation and fragmentation related parameters include an aggregation distribution coefficient between any two bubbles, a fragmentation distribution coefficient between any two bubbles, a coalescence probability between any two bubbles, and a fragmentation probability of each bubble.
The number density determining module 304 is specifically configured to, when determining the bubble aggregation and fragmentation related parameter according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume, and the bubble migration related parameter:
and inputting the current actual volume and the calculated volume of each bubble into a preset aggregation distribution coefficient algorithm to determine an aggregation distribution coefficient between any two bubbles. And determining the coalescence probability between any two bubbles and the breakage probability of each bubble according to the diameter of each bubble, the current migration speed of each bubble, the bubble migration related parameters and a preset coalescence probability algorithm. And determining the sub-bubble size distribution coefficient of each bubble according to the breaking probability of each bubble and a preset distribution coefficient algorithm. And determining the fragmentation distribution coefficient between any two bubbles according to the current actual volume, the calculated volume, the sub-bubble size distribution coefficient and a preset fragmentation distribution coefficient algorithm of each bubble.
Optionally, in this embodiment, the bubble migration related parameter includes an aggregation calculation coefficient and a volume type total amount into which the bubble volume is divided.
The preset number density algorithm is as follows:
wherein the N term represents the current number density, u b Represents the current migration velocity of the bubbles, δ represents the aggregation calculation coefficient, η represents the aggregation distribution coefficient between any two bubbles, ζ represents the fragmentation distribution coefficient between any two bubbles, c represents the coalescence probability between any two bubbles, b represents the fragmentation probability of the bubbles, t represents time, i, j, and k represent different bubbles, respectively, and M represents the total volume type into which the bubble volume is divided.
Optionally, in this embodiment, the apparatus 400 for determining the number density of bubbles in the pipeline further includes:
and a long air bag determining module 401 for obtaining the cross-sectional area of the target region of the target conduit. And determining the total cross-sectional area of the bubbles in the target area according to the diameter of each bubble in the target area and the number density of the corresponding bubble. It is determined whether a quotient between the total cross-sectional area of the bubble and the cross-sectional area of the target conduit is greater than or equal to a preset threshold. And if the quotient is larger than or equal to the preset threshold value, determining that the long air bag exists in the target area of the target pipeline.
The device for determining the number and density of bubbles in a pipeline provided in this embodiment may implement the technical solutions of the method embodiments shown in fig. 2 to 6, and the implementation principle and technical effects thereof are similar to those of the method embodiments shown in fig. 2 to 6, and are not described in detail herein.
The invention also provides an electronic device, a computer readable storage medium and a computer program product according to the embodiments of the invention.
As shown in fig. 9, fig. 9 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention. Electronic devices are intended for various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 9, the electronic apparatus includes: a processor 501 and a memory 502. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device.
The memory 502 is a non-transitory computer readable storage medium provided by the present invention. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the method for determining the number density of bubbles in the pipeline provided by the present invention. The non-transitory computer-readable storage medium of the present invention stores computer instructions for causing a computer to execute the method for determining the number density of pipeline bubbles provided by the present invention.
The memory 502, which is a non-transitory computer-readable storage medium, may be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as program instructions/modules corresponding to the method for determining the number density of bubbles in a pipeline according to the embodiment of the present invention (for example, the acquiring module 301, the outputting module 302, the speed determining module 303, and the number density determining module 304 shown in fig. 7). The processor 501 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 502, so as to implement the method for determining the number density of bubbles in the pipeline in the above method embodiment.
Meanwhile, the present embodiment also provides a computer product, and when instructions in the computer product are executed by a processor of an electronic device, the electronic device is enabled to execute the method for determining the number density of bubbles in the pipeline according to the first embodiment or the second embodiment.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the embodiments of the invention following, in general, the principles of the embodiments of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the embodiments of the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the embodiments of the invention being indicated by the following claims.
It is to be understood that the embodiments of the present invention are not limited to the precise arrangements described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of embodiments of the invention is limited only by the appended claims.
Claims (10)
1. A method for determining the bubble number density of a pipeline is characterized by comprising the following steps:
acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline;
inputting the fluid mechanics parameters into a preset double-fluid model to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline;
determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm;
and determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm.
2. The method of claim 1, wherein the preset bubble migration velocity algorithm comprises: a bubble buoyancy algorithm and a bubble drag force algorithm;
the determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm comprises:
determining the bubble diameter corresponding to each bubble according to the current actual volume of each bubble;
inputting the fluid mechanics parameter and the bubble diameter into the bubble buoyancy algorithm to output the buoyancy borne by the bubble;
inputting the fluid mechanics parameter, the bubble diameter, the current liquid phase flow rate and the current gas phase flow rate into the bubble drag force algorithm to output the liquid flow drag force applied to the bubble;
and determining the current migration speed of the bubbles according to the buoyancy force borne by the bubbles and the liquid flow dragging force borne by the bubbles.
3. The method according to claim 2, wherein the determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble and a preset number density algorithm comprises:
determining a corresponding calculated volume according to the current actual volume of each bubble and a preset conversion algorithm;
determining bubble polymerization crushing related parameters according to the diameter of each bubble, the current migration speed, the calculated volume, the current actual volume and bubble migration related parameters;
and inputting the current migration speed of each bubble, the bubble aggregation and fragmentation related parameters and the bubble migration related parameters into a preset number density algorithm to determine the current number density of the bubbles in the target pipeline.
4. The method of claim 3, wherein the bubble aggregation collapse related parameters comprise an aggregation distribution coefficient between any two bubbles, a collapse distribution coefficient between any two bubbles, an aggregation probability between any two bubbles, and a collapse probability of each bubble;
the determining of the bubble polymerization and fragmentation related parameters according to the diameters of the bubbles, the current migration speed, the calculated volume, the current actual volume and the bubble migration related parameters comprises:
inputting the current actual volume and the calculated volume of each bubble into a preset aggregation distribution coefficient algorithm to determine an aggregation distribution coefficient between any two bubbles;
determining the coalescence probability between any two bubbles and the breakage probability of each bubble according to the diameter of each bubble, the current migration speed of each bubble, the bubble migration related parameters and a preset coalescence probability algorithm;
determining the sub-bubble size distribution coefficient of each bubble according to the breaking probability of each bubble and a preset distribution coefficient algorithm;
and determining the breaking distribution coefficient between any two bubbles according to the current actual volume of each bubble, the calculated volume, the sub-bubble size distribution coefficient and a preset breaking distribution coefficient algorithm.
5. The method of claim 4, wherein the bubble migration related parameters include an aggregation calculation coefficient and a volume type total amount into which the bubble volume is divided;
the preset number density algorithm is as follows:
wherein the term N represents the current number density, u b RepresentsThe current migration speed of the bubbles, delta represents an aggregation calculation coefficient, epsilon represents an aggregation distribution coefficient between any two bubbles, delta represents a fragmentation distribution coefficient between any two bubbles, c represents an aggregation probability between any two bubbles, b represents a fragmentation probability of the bubbles, t represents time, i, j and k represent different bubbles respectively, and M represents the total volume type of the bubbles.
6. The method according to any one of claims 2 to 5, wherein after determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameter, the current migration speed of each bubble and a preset number density algorithm, the method further comprises:
acquiring the sectional area of a target pipeline;
determining the total cross-sectional area of the bubbles in the target area according to the diameter of each bubble in the target area and the number density of the corresponding bubble;
determining whether a quotient between the total cross-sectional area of the bubble and the cross-sectional area of the target conduit is greater than or equal to a preset threshold;
and if the quotient is determined to be greater than or equal to a preset threshold value, determining that the long air bag exists in the target area of the target pipeline.
7. A bubble number density determining apparatus for a pipeline, comprising:
the acquisition module is used for acquiring the current actual volume, the fluid mechanics parameter and the bubble migration related parameter of each bubble in the target pipeline;
the output module is used for inputting the fluid mechanics parameters into a preset double-fluid model so as to output the current liquid phase flow rate and the current gas phase flow rate of the fluid in the target pipeline;
the speed determining module is used for determining the current migration speed of each bubble according to the current actual volume of each bubble, the hydrodynamic parameter, the current liquid phase flow rate, the current gas phase flow rate and a preset bubble migration speed algorithm;
and the number density determining module is used for determining the current number density of the bubbles in the target pipeline according to the current actual volume of each bubble, the bubble migration related parameters, the current migration speed of each bubble and a preset number density algorithm.
8. An electronic device, comprising: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the method of determining a number density of bubbles in a conduit according to any one of claims 1 to 6 by the processor.
9. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, are configured to implement the method of determining a bubble number density of a pipeline according to any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, carries out the method for determining the number density of bubbles in a conduit according to any one of claims 1 to 6.
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| CN202110837430.9A CN115688615A (en) | 2021-07-23 | 2021-07-23 | Method, device, equipment, medium and product for determining number density of pipeline bubbles |
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| CN117454063B (en) * | 2023-12-26 | 2024-03-12 | 西南石油大学 | Wellbore oil-gas-water multiphase flow state discrimination and water holdup calculation method |
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