CN113673179A - Long-distance slurry pipeline conveying dynamic model and application - Google Patents

Long-distance slurry pipeline conveying dynamic model and application Download PDF

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CN113673179A
CN113673179A CN202110851165.XA CN202110851165A CN113673179A CN 113673179 A CN113673179 A CN 113673179A CN 202110851165 A CN202110851165 A CN 202110851165A CN 113673179 A CN113673179 A CN 113673179A
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王费新
周忠玮
邢津
鲁嘉俊
程书凤
尹纪富
庄海飞
刘功勋
袁超哲
冒小丹
洪国军
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CCCC National Engineering Research Center of Dredging Technology and Equipment Co Ltd
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Abstract

The invention discloses a long-distance slurry pipeline conveying dynamic model and application thereof. Hydraulic transport is the main form of silt transport in dredging projects. At present, the mud pump and the pipeline system are mostly matched based on quasi-static matching of performance characteristics of the mud pump and the pipeline system, and influence of fluctuation of working parameters and redistribution of dredged objects in an actual conveying process on the performance characteristics of the whole system is not considered, so that certain problems may exist for a long-distance high-concentration conveying working condition. Therefore, the invention is based on the conveying process of a certain cutter suction dredger on a certain construction site, measures a large amount of site test data, establishes a set of complete dynamic conveying theoretical model and verifies the model.

Description

Long-distance slurry pipeline conveying dynamic model and application
Technical Field
The invention belongs to the field of hydraulic conveying, and is applied to dredging engineering.
Background
In dredging engineering, the main form of silt transportation is hydraulic transportation, especially long-distance pipeline transportation of solid-liquid mixed multiphase flow, and a multi-pump system is often used. Pipeline transportation has a great influence on dredging construction efficiency and construction cost, and is characterized in that great energy consumption is generated in the pipeline transportation process, for example, in the construction of a cutter suction dredger, the pipeline transportation energy consumption accounts for more than 80% of the total energy consumption. The increase in the slurry flow rate leads to an increase in friction and an increase in energy consumption. Too fast a slurry flow rate can result in wasted energy; and the slurry flow velocity is too slow, so that silt is deposited in the pipeline, and a series of problems of pipe blockage, pipe explosion and the like are caused. Achieving efficient, stable, and safe hydraulic delivery is a constantly sought goal.
At present, the research on the performance characteristics of a dredge pump-pipeline conveying system more shows a quasi-static characteristic, namely, the research on the performance characteristics of the dredge pump and the pipeline conveying characteristics is carried out independently. The matching of the dredge pump and the pipeline system is also quasi-static matching based on the performance characteristics of the dredge pump, and the influence of the fluctuation of working parameters in the actual conveying process and the redistribution of dredged materials in the pipeline on the performance characteristics of the whole system is not considered. The mode is feasible under the working conditions that the fluctuation of the conveying parameters is small and the conveying flow rate is larger than the critical flow rate, but certain problems can exist in the working conditions of long-distance high-concentration conveying and large concentration fluctuation. Panding (2015) establishes a quasi-static pipeline transportation model which cannot simulate the state of slurry in the whole pipeline and reflect the dynamic characteristics of the slurry.
Therefore, the theoretical model established by researchers at present is not perfect enough, and the dynamic characteristic of the whole pipeline for conveying the slurry cannot be well researched.
Disclosure of Invention
One of the purposes of the application is to provide a set of conveying dynamic theoretical model, namely, a research result of dynamic characteristics of the whole slurry conveying in a long-distance pipeline is disclosed in the field, and the fluctuation of each working parameter and the influence rule of the redistribution of the dredged objects on the performance characteristics of the whole system in the actual conveying process are obtained.
A second object of the present application is to provide an application of the above dynamic theoretical model in dredging engineering in the field. Because the theoretical model can approximately simulate the macroscopic dynamic conveying process of the solid-liquid two-phase flow in the long-distance pipeline, the key fluid physical quantity can be calculated in real time in a long-distance pump-pipeline hydraulic conveying system blown by the drag suction dredger bank and the drag suction dredger bow, thereby predicting the conveying operation safety of the pipeline system.
Therefore, the technical scheme of the invention is as follows:
a dynamic theoretical model based on long-distance slurry pipeline transportation is characterized in that the theoretical model comprises a friction resistance I of a slurry transportation pipelinemThe formula is as follows:
Figure BDA0003182387900000021
Figure BDA0003182387900000022
Figure BDA0003182387900000023
in the formula (I), the compound is shown in the specification,
Imfor conveying slurry friction loss (mH)2O/m); alpha is a correction coefficient related to the relative viscosity coefficient of the slurry; vssThe settling velocity of silt particles is shown;
lambda is the on-way resistance coefficient of the pipeline when clean water is conveyed; v is the conveying flow velocity (m/s); g is gravity acceleration (m/s)2) (ii) a D is the inner diameter (m) of the pipeline; gamma raymIs volume weight (t/m) of slurry3)；γwFor delivering the volume weight (t/m) of the carrier liquid3)；γsIs solid volume weight (t/m)3)；KmThe test coefficient is determined by actually measured data, and the value is 1120; mu.ssThe coefficient of friction is generally 0.44; cvdIs the volume concentration of solid particles in the slurry;
re is reynolds number (dimensionless number); delta is the equivalent roughness of the tube wall;
Vcfor the critical flow rate (m/s), the canonical formula (JTS 181-5-2012), which is already known in the art, was chosen, so the individual parameters are left out of the notation:
Vc＝(90CV)1/3·g1/4·D1/2·ω1/2·dm -1/4 (6)
furthermore, the theoretical model also includes the total on-way head loss hmInlet head loss hjmOutlet head loss hjouHead loss h of climbingHTotal head loss h of pipelinemt(ii) a Total on-way head loss hmThe total head loss h of each pipeline section along the way is the total head loss h of the pipelinemtIs the sum of all head losses;
their calculation formulas are respectively as follows:
hm＝∑(Im·L·k) (7)
Figure BDA0003182387900000024
Figure BDA0003182387900000025
Figure BDA0003182387900000026
in the formula, k is a length conversion coefficient and is determined by the type of the pipeline; l is the length of each pipe section; xiinIs the inlet head loss coefficient, ξoutOutlet head loss coefficient; the inlet of the pipeline is an expanding opening, the outlet of the pipeline is a reducing opening, vinIs the inlet velocity, voutIs the exit velocity; hdown，Htide，HupRespectively digging depth, tide level and climbing height of a pipeline on the land for the cutter suction dredger; gamma raymThe density of the slurry is converted by concentration, and the formula is as follows:
γm＝(γs-γw)·Cvd+γw (11)
total head loss h of pipelinemt：
hmt＝hjin+hjout+hH+hm (12)
Furthermore, the theoretical model also comprises a corresponding instantaneous clear water lift H under a certain slurry flow rate conditionw1The lift H of the mud pump under the condition of certain slurry concentrationm；
The reasoning process is as follows;
the clear water rated lift H of the underwater pump and the cabin pump used by the shipweRated flow Q of fresh waterweThe relation is fitted by a polynomial and respectively satisfies the following relations:
Figure BDA0003182387900000031
rated speed n of underwater pumpwe1The rated rotation speeds of the pumps in the two cabins are both nwe2(ii) a Flow rate Q of slurryw1-dredge pump speed nw1The following relationships exist:
Figure BDA0003182387900000032
the corresponding rated clean water lift H is obtained by the formula (13)we；
The mud pump with a certain flow rate Q is obtained by the formula (14)w1Rotational speed nw1Lower corresponding rated clear water flow Qwe；
Rated clean water lift HweAnd instantaneous clear water lift Hw1And satisfies the following relation:
Figure BDA0003182387900000033
thus, the corresponding instantaneous clear water lift H under the condition of certain slurry flow is calculatedw1；
According to the Stepanoff empirical formula, the head drop ratio HR is expressed as:
HR＝1-(0.8+0.6logdm)·Cvd (16)
in the formula (d)mIs the average particle diameter of slurry particles, CvdIs the volume concentration of the slurry;
meanwhile, the head lowering ratio HR is expressed as:
Figure BDA0003182387900000034
by integrating the formulas (16) to (17), the lift H of the mud pump under the condition of certain slurry concentration is obtainedm；
Furthermore, the theoretical model also comprises the total mass M of the slurry in the pipeline, the acceleration a of the slurry and the flow velocity V of the slurry at the current momentt；
Their formula and reasoning process are:
Figure BDA0003182387900000035
the slurry acceleration a is:
Figure BDA0003182387900000041
then at the next moment, the slurry flow velocity Vt+1Is composed of
Vt+1＝Vt+a (20)
In the formula, VtIs the slurry flow rate at the present moment.
An application based on a long-distance mud pipeline conveying dynamic model comprises the following steps:
firstly, based on the assumption that the slurry concentration does not change along with the change of the spatial position, the Lagrange method is proposed to deduce the concentration displacement distance and the concentration distribution in the whole pipeline, and the initialization is completed by utilizing the actually measured concentration and the flow velocity to calculate a pipeline theory model;
and secondly, calculating the total head loss and the total lift of the mud pump of the whole pipeline according to the theoretical model based on the initial concentration distribution and the initial flow velocity of the whole pipeline from a certain moment, and calculating the acceleration of the slurry by using the total head difference and the total mass of the slurry to obtain the flow velocity of the slurry at the next moment.
The Lagrange method deduces the concentration displacement distance and the concentration distribution in the whole pipeline, and specifically comprises the following steps: the actually measured concentration of the slurry at the suction port of the pipeline at a certain moment is c, the actually measured flow velocity v of the slurry is a function of time, and after delta t time, the slurry with the concentration of c is positioned at a position x away from the suction port:
Figure BDA0003182387900000042
i.e. to obtain a concentration profile over the entire pipe.
Drawings
FIG. 1 is a schematic diagram of the arrangement of sludge discharge pipelines under the construction condition of a certain cutter suction dredger
FIG. 2 is a graph showing the measured flow rate and the measured wet concentration over time within a certain cut-off period
FIG. 3 is a graph of measured instantaneous wet square output over time over a cut-out period
FIG. 4 is a graph showing the distribution of the slurry concentration along the length of the pipe at the 14000 th s time of the period
FIG. 5 is a graph comparing the concentration evolution result of the second stage of pipe section with the measured differential pressure
FIG. 6 comparison graph of pipeline flow rate, concentration prediction and actual measurement
FIG. 7 comparison graph of prediction and actual measurement of water head of on-way piezometer tube
Detailed Description
The detailed description will be disclosed in the paper; the technical scheme of the application has patentability.
Theoretical model:
selecting a equation of Fer and auspicious (1994) as a basic equation, correcting the equation through actually measured data, and performing friction resistance I on the pipelinemCalculating; the modified equation of auspicious is as follows:
Figure BDA0003182387900000051
Figure BDA0003182387900000052
Figure BDA0003182387900000053
in the formula (I), the compound is shown in the specification,
Imfor conveying slurry friction loss (mH)2O/m); alpha is a correction coefficient related to the relative viscosity coefficient of the slurry; vssThe settling velocity of silt particles is shown;
lambda is the on-way resistance coefficient of the pipeline when clean water is conveyed; v is the conveying flow velocity (m/s); g is gravity acceleration (m/s)2) (ii) a D is the inner diameter (m) of the pipeline; gamma raymIs volume weight (t/m) of slurry3)；γwFor delivering the volume weight (t/m) of the carrier liquid3)；γsIs solid volume weight (t/m)3)；KmThe test coefficient is determined by actually measured data, and the value is 1120; mu.ssThe coefficient of friction is generally 0.44; cvdVolume of solid particles in the slurryConcentration;
re is reynolds number (dimensionless number); and delta is the equivalent roughness of the tube wall.
VcFor the critical flow rate (m/s), the canonical formula (JTS 181-5-2012), which is already known in the art, was chosen, so the individual parameters are left out of the notation:
Vc＝(90CV)1/3·g1/4·D1/2·ω1/2·dm -1/4 (6)
due to the length L of each section of pipeline and the corresponding slurry concentration CvdThe flow velocity v is different at each moment, so the friction resistance value I of each pipeline at each momentmAll different, the corresponding head losses are different.
In the working condition used by the invention, the inner diameters of the marine pipe, the floating pipe on the water, the underwater immersed pipe and the shore pipe on the land are consistent, and the length conversion coefficient of each pipe section can be obtained according to the conversion ratio and the conversion length ratio of the local resistance, which is shown in a table 3.
TABLE 3 conversion factor k for each pipe length
Figure BDA0003182387900000054
Total on-way head loss hmIs the sum of head loss along the way of each section of pipeline:
hm＝∑(Im·L·k) (7)
in addition, the inlet head loss hjmLoss of outlet head hjouHigh head loss hHThe calculation formulas are respectively as follows:
Figure BDA0003182387900000061
Figure BDA0003182387900000062
Figure BDA0003182387900000063
in the formula, the inlet head loss coefficient xiinThe value is 0.8, and the outlet head loss coefficient xioutTaking the value as 1; the inlet of the pipeline is a flaring with the diameter of the cross section of 0.9m and the inlet velocity vinConversion is carried out through the sectional area ratio; the outlet is a necking, the diameter of the cross section is 0.45m, and the outlet velocity voutConverted by the outlet cross-sectional area ratio. Hdown，Htide，HupThe values of the cutter suction dredger in the calculation time interval are respectively 25m, 0.41m and 8m, wherein the depth is dug by the cutter suction dredger, the sea level is tidal level and the pipeline is climbed on the land. Gamma raymThe density of the slurry mixture was calculated by concentration, and the formula is as follows.
γm＝(γs-γw)·Cvd+γw (11)
Total head loss h of pipelinemtAs the sum of all head losses:
hmt＝hjin+hjout+hH+hm (12)
the clear water rated lift H of the underwater pump and the cabin pump used by the shipweRated flow Q of fresh waterweThe relationship is fitted by a polynomial expression, and the following relational expressions are satisfied respectively.
Figure BDA0003182387900000064
Rated speed n of underwater pumpwe1245r/min, the rated speed of the pump in the two cabins is nwe2257 r/min. Flow rate Q of slurryw1-dredge pump speed nw1The following relationships exist:
Figure BDA0003182387900000065
the mud pump can obtain a certain flow rate Q through the formula (14)w1Rotational speed nw1Lower corresponding rated clear water flow Qwe. The corresponding amount is obtained through the relation (13)Fixed clear water lift Hwe. Rated clean water lift HweAnd instantaneous clear water lift Hw1And satisfies the following relation:
Figure BDA0003182387900000066
thus, the corresponding instantaneous clear water lift H under the condition of certain slurry flow can be calculatedw1。
According to the Stepanoff empirical formula, the head-to-fall ratio HR can be expressed as:
HR＝1-(0.8+0.6logdm)·Cvd (16)
in the formula (d)mThe median particle diameter d is used according to the invention for the average particle diameter of the slurry particles50Alternative, CvdIs the slurry volume concentration.
Meanwhile, the head drop ratio HR can also be expressed as:
Figure BDA0003182387900000071
by integrating the formulas (16) to (17), the lift H of the mud pump under the condition of certain slurry concentration can be obtainedm。
The total mass M of the slurry in the pipeline is as follows:
Figure BDA0003182387900000072
the slurry acceleration a is:
Figure BDA0003182387900000073
then at the next moment, the slurry flow velocity Vt+1Is composed of
Vt+1＝Vt+a (20)
In the formula, VtIs the slurry flow rate at the present moment.
Field test
Taking a certain site construction of a certain cutter suction ship as an example, a series of data are measured, including real-time slurry concentration and flow rate measured on the cutter suction ship, pipe internal pressure at a key node, dredge pump parameters, pipeline geometric parameters, row spacing and the like. As shown in fig. 1, the arrangement of the mud pipes under the construction condition is shown.
The water top pipe mainly comprises a floating sheet pipe and an armor pipe, the land pipe mainly comprises a polyurethane pipe and a steel pipe, the roughness delta of each pipe is different, and the roughness measured values are shown in table 1. Set up 4 pressure monitoring points along the pipeline on water altogether, its elevation changes along with the tide level, and the bank top pipe has set up 6 pressure monitoring points altogether, and pressure measurement point position and elevation are seen table 2. Except the inlet and the outlet, the inner diameters of all the pipelines are 0.85m, and the total length of the pipeline is 2495.5 m.
TABLE 1 roughness Delta of different pipe materials
Figure BDA0003182387900000074
TABLE 2 onshore pipeline pressure measurement Point location (distance from Density measurement Point) and elevation
Figure BDA0003182387900000075
Here, the real-time particle volume concentration, slurry flow rate and instantaneous excavation yield (volume of excavation per unit time) measured over a certain period of time are mainly given. A certain time period was chosen for the analysis studies, as shown in figures 2 and 3, for the concentration, flow rate and instantaneous production measured at the measurement points on the vessel, respectively.
In the working condition, the conveying medium is medium coarse sand, and the median particle diameter d is tested50Is 0.7 mm. Selecting a Wushu formula to carry out silt particle sedimentation velocity VssThe calculation of (2):
Figure BDA0003182387900000081
wherein v is the motion viscosity coefficient and takes the value of 10-6m2S; g is the acceleration of gravity, and is 9.8m/s2；γsThe volume weight of solid materials is conveyed, the working condition used by the specific embodiment is mainly medium coarse sand, and 2.65t/m is taken3；γwIs the volume weight of the conveying medium, mainly seawater, 1.025t/m3。
Model assumptions and validation thereof
On-site measurement is difficult to install concentration meters on the whole pipeline, slurry concentration measurement and flow velocity measurement are often selected to be carried out on a certain section of suitable pipeline on a ship deck, flow is consistent on all sections of the whole pipeline, but is influenced by a dredger operation mode, underwater topography, soil conditions and other factors, concentration change is complex, distribution of the concentration in the whole pipeline is uneven, and in order to obtain friction resistance, critical flow velocity and the like of the whole pipeline, concentration obtained by a measuring point on a ship needs to be deduced on the whole pipeline to obtain concentration distribution of the whole pipeline.
For engineering safety reasons, the slurry flow rate is often controlled to be above a critical flow rate to reduce sediment deposition and prevent pipe plugging. Therefore, it is assumed that the concentration value of the slurry does not change with the change of the spatial position during the transportation. Taking the example of a slurry at the suction opening of the conduit at a certain time, the slurry concentration c, as the slurry flow rate v varies with time, which can be considered as a function of time, the distance moved by the slurry at that concentration per second is not the same, and after Δ t the slurry is at a distance x from the suction opening, which can be expressed as:
Figure BDA0003182387900000082
and by analogy, obtaining the concentration distribution on the whole pipeline. This calculation method is very similar to the lagrangian method in fluid mechanics. Discretizing time in seconds, and tracking each concentration value and the displacement distance of the concentration value on the pipeline at each moment. Therefore, the interval distance between the tracked concentration values is different, the concentration at the interval length between the two concentrations is obtained by interpolation, the verification example uses a rectangular interpolation method for approximate calculation, and the pipe section length L is the interval length here. It should be noted that although the total length of the pipeline is fixed, the total number of the pipe sections is not the same, and the number of the integration sections is also changed when the discrete integration is performed, so that when the summation calculation in the length is performed, the upper and lower summation limits are not given for simplifying the expression.
And calculating the concentration distribution of the whole pipeline in sequence by taking the concentration and flow rate measurement positions as zero points of the pipeline and taking the concentration and flow rate measurement values measured at the points as the basis, thereby completing the initialization of the concentration and flow rate calculated by the theoretical model. The data in a certain 25000s period is selected for analysis, and the estimated concentration distribution result is shown in fig. 4 by taking the 14000s time of the period as an example. Meanwhile, for a certain section of pipeline, the pressure difference change rule of the pipeline is in accordance with the average concentration change rule, the pipeline section between the pressure measurement point bank 4 and the pressure measurement point bank 5 is selected for analysis, and the actually measured pressure difference and the concentration calculated by the pipeline section are compared after normalization processing is carried out, so that the accuracy of the concentration calculation method is verified. The result of the comparison between the concentration evolution result on the monitoring pipe section and the measured differential pressure is shown in fig. 5. The two are well matched, which shows that the concentration distribution estimated based on the assumption is more accurate and can be used as the basis for the later dynamic model derivation.
Results and analysis:
(1) the flow rate and concentration prediction results are shown in a figure 6 pipeline flow rate, concentration prediction and actual measurement comparison graph.
Two periods of time are respectively selected as two working conditions, the flow rate is calculated and predicted, and the calculation result is shown in fig. 6. The black curve is the measured flow rate, the red curve is the calculated flow rate, and the blue curve is the predicted average concentration. In the two working conditions, the predicted flow rate and the actually measured flow rate have basically the same trend, and the accuracy of the model is verified. The predicted flow rate is substantially inversely related to the predicted average concentration. It can be seen that the flow rate is greatly influenced by concentration, the instantaneous concentration of the suction port is increased when the excavation yield is increased, if the yield is kept high for a period of time, the average concentration of the pipeline is increased, the pipe resistance is increased, and the flow rate is reduced; and vice versa. The flow velocity prediction has positive significance for actual construction, for example, the critical flow velocity of a certain section of pipeline can be calculated through the flow velocity and the average concentration of the section of pipeline, whether the critical flow velocity has the risk of deposition blockage or not is predicted, if the flow velocity is too low, a constructor can be prompted to increase the rotating speed of a mud pump so as to improve the flow velocity, the model predicts the future flow velocity, the influence of rotating speed adjustment on the flow velocity can be predicted, and the constructor is guided to adjust the rotating speed.
(2) The pressure change results are shown in FIG. 7 along the way of the prediction and actual measurement comparison graph of the piezometric tube head.
In fig. 7, the pressure curve is a predicted pressure curve of the piezometer tube, the starting position is where the concentration is measured, and the end point is the outlet of the sludge discharge tube. The pressure at the starting position is the greatest, substantially close to the total head of the three pumps, and the pressure at the outlet position is substantially zero. In the figure, 4 pressure measuring points are arranged on the water pipe, 6 pressure measuring points are arranged on the shore pipe, the measured pressure value and the position of the pressure value are marked by discrete points, and the calculated value is basically consistent with the measured value, so that the accuracy of the model is verified. By utilizing the pressure curve, the pressure distribution situation on the whole pipeline can be clearly known, and the pressure drop situations of different pipelines can also be known. It should be noted that the manometric tube pressure curve should not be a straight line as shown in the figure in the sink leg, but is not shown as practical since the sink leg is not taking pressure measurements.

Claims (3)

1. A dynamic theoretical model based on long-distance slurry pipeline transportation is characterized in that the theoretical model comprises a friction resistance I of a slurry transportation pipelinemThe formula is as follows:
Figure FDA0003182387890000011
Figure FDA0003182387890000012
Figure FDA0003182387890000013
in the formula (I), the compound is shown in the specification,
Imfor conveying slurry friction loss (mH)2O/m); alpha is a correction coefficient related to the relative viscosity coefficient of the slurry; vssThe settling velocity of silt particles is shown;
lambda is the on-way resistance coefficient of the pipeline when clean water is conveyed; v is the conveying flow velocity (m/s); g is gravity acceleration (m/s)2) (ii) a D is the inner diameter (m) of the pipeline; gamma raymIs volume weight (t/m) of slurry3)；γwFor delivering the volume weight (t/m) of the carrier liquid3)；γsIs solid volume weight (t/m)3)；KmThe test coefficient is determined by actually measured data, and the value is 1120; mu.ssThe coefficient of friction is generally 0.44; cvdIs the volume concentration of solid particles in the slurry;
re is reynolds number (dimensionless number); delta is the equivalent roughness of the tube wall;
Vcfor the critical flow rate (m/s), the canonical formula (JTS 181-5-2012), which is already known in the art, was chosen, so the individual parameters are left out of the notation:
Vc＝(90CV)1/3·g1/4·D1/2·ω1/2·dm -1/4 (6)
furthermore, the theoretical model also includes the total on-way head loss hmInlet head loss hjmOutlet head loss hjouHead loss h of climbingHTotal head loss h of pipelinemt(ii) a Total on-way head loss hmThe total head loss h of each pipeline section along the way is the total head loss h of the pipelinemtIs the sum of all head losses;
their calculation formulas are respectively as follows:
hm＝∑(Im·L·k) (7)
Figure FDA0003182387890000014
Figure FDA0003182387890000015
Figure FDA0003182387890000016
in the formula, k is a length conversion coefficient and is determined by the type of the pipeline; l is the length of each pipe section; xiinIs the inlet head loss coefficient, ξoutOutlet head loss coefficient; the inlet of the pipeline is an expanding opening, the outlet of the pipeline is a reducing opening, vinIs the inlet velocity, voutIs the exit velocity; hdown，Htide，HupRespectively digging depth, tide level and climbing height of a pipeline on the land for the cutter suction dredger; gamma raymThe density of the slurry is converted by concentration, and the formula is as follows:
γm＝(γs-γw)·Cvd+γw (11)
total head loss h of pipelinemt：
hmt＝hjin+hjout+hH+hm (12)
Furthermore, the theoretical model also comprises a corresponding instantaneous clear water lift H under a certain slurry flow rate conditionw1The lift H of the mud pump under the condition of certain slurry concentrationm；
The reasoning process is as follows;
the clear water rated lift H of the underwater pump and the cabin pump used by the shipweRated flow Q of fresh waterweThe relation is fitted by a polynomial and respectively satisfies the following relations:
Figure FDA0003182387890000021
rated speed n of underwater pumpwe1The rated rotation speeds of the pumps in the two cabins are both nwe2(ii) a Flow rate Q of slurryw1-dredge pump speed nw1The following relationships exist:
Figure FDA0003182387890000022
the corresponding rated clean water lift H is obtained by the formula (13)we；
The mud pump with a certain flow rate Q is obtained by the formula (14)w1Rotational speed nw1Lower corresponding rated clear water flow Qwe；
Rated clean water lift HweAnd instantaneous clear water lift Hw1And satisfies the following relation:
Figure FDA0003182387890000023
thus, the corresponding instantaneous clear water lift H under the condition of certain slurry flow is calculatedw1；
According to the Stepanoff empirical formula, the head drop ratio HR is expressed as:
HR＝1-(0.8+0.6logdm)·Cvd (16)
in the formula (d)mIs the average particle diameter of slurry particles, CvdIs the volume concentration of the slurry;
meanwhile, the head lowering ratio HR is expressed as:
Figure FDA0003182387890000024
by integrating the formulas (16) to (17), the lift H of the mud pump under the condition of certain slurry concentration is obtainedm；
Furthermore, the theoretical model also comprises the total mass M of the slurry in the pipeline, the acceleration a of the slurry and the flow velocity V of the slurry at the current momentt；
Their formula and reasoning process are:
Figure FDA0003182387890000031
the slurry acceleration a is:
Figure FDA0003182387890000032
then at the next moment, the slurry flow velocity Vt+1Is composed of
Vt+1＝Vt+a (20)
In the formula, VtIs the slurry flow rate at the present moment.
2. The application of the dynamic model based on the long-distance mud pipeline transportation is characterized by comprising the following steps:
firstly, based on the assumption that the slurry concentration does not change along with the change of the spatial position, the Lagrange method is proposed to deduce the concentration displacement distance and the concentration distribution in the whole pipeline, and the initialization is completed by utilizing the actually measured concentration and the flow velocity to calculate a pipeline theory model;
and secondly, calculating the total head loss and the total lift of the mud pump of the whole pipeline according to the theoretical model based on the initial concentration distribution and the initial flow velocity of the whole pipeline from a certain moment, and calculating the acceleration of the slurry by using the total head difference and the total mass of the slurry to obtain the flow velocity of the slurry at the next moment.
3. The application of the long-distance mud pipeline transportation dynamic model according to claim 2,
the Lagrange method deduces the concentration displacement distance and the concentration distribution in the whole pipeline, and specifically comprises the following steps: the actually measured concentration of the slurry at the suction port of the pipeline at a certain moment is c, the actually measured flow velocity v of the slurry is a function of time, and after delta t time, the slurry with the concentration of c is positioned at a position x away from the suction port:
Figure FDA0003182387890000033
i.e. to obtain a concentration profile over the entire pipe.
CN202110851165.XA 2021-07-27 2021-07-27 Long-distance slurry pipeline conveying dynamic model and application Pending CN113673179A (en)

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CN117236055A (en) * 2023-10-10 2023-12-15 中煤科工集团武汉设计研究院有限公司 Method for calculating blocking critical condition of slurry pipeline
CN117246772A (en) * 2023-08-07 2023-12-19 中交疏浚技术装备国家工程研究中心有限公司 Jet flow air-entraining system and method for slurry conveying pipeline

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115293071A (en) * 2022-09-28 2022-11-04 中南大学 Method and device for measuring and calculating water head of water-rich tunnel stratum based on outlet flow characteristics of drain holes
CN115293071B (en) * 2022-09-28 2022-12-20 中南大学 Method and device for measuring and calculating water head of water-rich tunnel stratum based on outlet flow characteristics of drain holes
CN116362162A (en) * 2023-05-30 2023-06-30 湖南百舸水利建设股份有限公司 Underwater high-concentration sludge conveying method, system, computer equipment and storage medium
CN116362162B (en) * 2023-05-30 2023-08-01 湖南百舸水利建设股份有限公司 Underwater high-concentration sludge conveying method, system, computer equipment and storage medium
CN117246772A (en) * 2023-08-07 2023-12-19 中交疏浚技术装备国家工程研究中心有限公司 Jet flow air-entraining system and method for slurry conveying pipeline
CN117236055A (en) * 2023-10-10 2023-12-15 中煤科工集团武汉设计研究院有限公司 Method for calculating blocking critical condition of slurry pipeline
CN117236055B (en) * 2023-10-10 2024-04-19 中煤科工集团武汉设计研究院有限公司 Method for calculating blocking critical condition of slurry pipeline

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