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Particle Movement Behavior in Drum Coal loading Process by Discrete

Element Method

Kuidong Gao 1.College of Mechanical & Electrical Engineering, Shandong University of

Science & Technology, Qingdao, Shandong, China 2.School of Mechanical & Electrical Engineering, China University of Mining &

Technology, Xuzhou, Jiangsu, China email: gaokuidong22@163.com

ABSTRACT Due to the restrictions of conditions, the movement of coal particle during drum coal loading process cannot be determined by test method only. In this paper, discrete element method was combined with test method to study the coal particle movement behavior. The particle mean velocity in X, Y, Z direction in drum envelope range was obtained under different simulation conditions. And the reason why mean velocity in X, Y, Z direction changed was analyzed emphatically. The relationship between the velocity and drum coal loading rate was also analyzed. Based on this, the influence of drum rotation speed on mechanism of drum coal loading with drum ejection and drum pushing was indicated, and provides a guide to drum structure design and working parameters selection. KEYWORDS: particle movement behavior; drum; coal loading; Discrete element method.

INTRODUCTION The drum coal loading process, the movement process of coal particle when drum works, has

an important influence on coal loading performance, but few scholar’s research involved it. By using computer technology, the drum coal loading performance under different working conditions was predicted well in C.J. Morris’s work[1]. The main factors that affected the shearer drum coal loading performance were indicated in the book named Longwall Mining written by S.S. Peng and H.S. Chiang[2]. The main effect factors of shearer drum coal loading performance were analyzed by M. Ayhan[3], noting the importance of a comfortable distance between coal wall and scrapers for coa loading performance. K.G. Hurt and F.G Mcstravick[4] pointed out that drum coal loading performance was affected by vane numbers, helix angle, vane depth, coal loading inlet size and drum rotation speed. Using the theoretical analysis and test methods, British scholars named J. Ludlow and an R.A. Jankowski[5] indicated that oversize wrap angle create the circulation of the coal increased the dust content; while wrap angle was too small , it was unfavourable for transporting the crushed coal to scraper conveyer. Through the test results, the main factors that influence drum coal loading performance were indicated and the optimum vane helical angle was determined by Liu Songyong and Gao Kuidong[6-9].

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UDEC, PLAXIS, FLAC and other finite element software can give helpless in the simulation of the bulk solid movement under the action of mechanism, although they can simulate the rock or soil crush[10,11]. Discrete Element Method software can solve this problem very well. Discrete Element Method [12,13], or DEM for short, as a numerical computation method was first used in rock structure simulation by P.A. Cundall in the 1980s[14,15]. With the development of technology for some decades, DEM has been widely applied in the research of geotechnical engineering and mechanical engineering[16-20]. Its application in helix conveyer is an important representative in mechanical engineering research[21,22]. The method of applying DEM in drum coal loading performance study was derived from its use in helix conveyer, and feasibility and accuracy of the method were proved in our previous studies.

According to the previous summary, the theoretical analysis and test methods were widely used in drum coal loading performance research. Due to the limitation of test conditions, accumulating mass could be analyzed statistical at the macro level only but the change of coal velocity couldn't be detected. So the particle velocity and distribution were studied by using PFC3D software in this paper, then the action mechanism of drum and coal particle was revealed.

CONTACT FORCE MODEL AND PARTICLE MOTION MODEL OF DEM

PFD3D provided many useful constitutive models, and these models were provided by Cundall[23], Mindlin and Deresiewicz[24],Schäfer et al. [25] and Walton[26]. But the linear spring-dashpot model is an exact and efficient model in field of screw conveyor simulation which proved by Shimizu and Cundall[27]. The spring-dashpot model was also used in our research, and it was shown in Fig.1

Spring (kn)

Dashpot(Cn)

Spring (kt)

Dashpot(Ct)

Slider

Figure 1: Linear spring-dashpot model

In spring-dashpot model, the contact can be simplified to three parts, such as a spring, a dashpot and a slider. The normal force Fn and the tangential force Ft were included in the contacts, and they were given by Eq(1) and Eq(2):

n n n nF k x C v= − ∆ + (1)

{ }t n t t tmin , d tF F k v t C vm= +∫ (2)

Vol. 21 [2016], Bund. 01 165 where, x∆ —amount of overlap; nk —spring stiffness between particles in normal direction; nC —normal damping coefficient between particles; nv —normal relative velocity between particles; m —frictional coefficient between particles; tC —tangential damping coefficient between particles; tk —spring stiffness between particles in tangential direction; tv —relative velocity between particles in tangential direction.

The motion of particle can be described in terms of its position, xi, velocity ix and acceleration, ix . According to newton’s second law, a particle motion can be expressed by Eq(3):

( )i iF m x g= − (3)

where m —mass of the particle, kg; iF —resultant force, N; g—gravity loading, m/s2.

The acceleration at time t can be described by Eq(4):

( ) [ ( / ) ( / )] /i i ix t x t t 2 x t t 2 t= + ∆ − −∆ ∆ (4)

The velocity at time( /t t 2+ ∆ ) can be described by Eq(5):

( / ) ( / ) ( ( ) / )i i i ix t t 2 x t t 2 F t m g t+ ∆ = −∆ + + ∆ (5)

Finally, the new position of particle can be determined by Eq(6):

( ) ( ) ( / )i i ix t t x t x t t 2 t+ ∆ = + + ∆ ∆ (6)

SIMULATION RESEARCH ON PARTICLE MOVEMENT BEHAVIOR

Cutting test bed for coal rock was shown in Fig.2. In this study, structure parameters of drum were chosen as follow: vane helix angle=21°, line spacing=30 mm, drum width= 330 mm, drum hub diameter= 200 mm, drum diameter= 530 mm, vane diameter= 420 mm, left helix hand. Combined simulation model of drum and coal wall which was proved its accuracy in previous works was shown in Fig.3. Particle parameters were chosen as follow: particle stiffness was 1x104 N/m, particle density was 1204.4 kg/m3, particle diameter was 30 mm, particle friction was 0.8. the coal wall parameters: wall stiffness was 1x107 N/m; wall friction was 0.58.

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Coal Wall

Drum

Feed Platform

Bearing Seat

Translation Platform

Gear Reducer

Torque SensorElectric Motor

Figure 2: Side view of cutting test bed for coal rock

Coal Wall

Bear Seat

Hauling Speed Direction

X

Z

Statistic Region I

Hauling Speed Direction

Bearing Seat

X

YStatistic

Region II

(a) Side view (b) Top view

Figure 3: Combined simulation model of drum and coal wall

To better reflect drum coal loading performance, the test was carried out after the drum excavating a half drum diameter opening. Some coal particles were piled up behind the drum and on the left of bearing seat during the opening work, which could affect the coal loading performance. So the stock pile of coal must be cleared before the test. In order to make the simulation consistent with the actual test, flow chart of drum coal loading simulation was shown in Fig.4.

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。

AreaII IArea

AreaII IArea

AreaII IArea

AreaII IArea

Build coal

loading process DEM model

Finish the first

step simulation

Delete the

particles in

area I

Finish the

secondstep

simulation

(1)Build rock cutting test bed DEM model;(2)Optimset wall parameters, particle parameters and drum working parameters;(3)Optimset primary simulation time T, T>half drum diameter/hauling speed;(4)Optimset the desired results.

Outputs the desired result dates

Stop the simulation; Delete the particles in area I; Continue the simulation until most particles were immobile.

Output dates of the particles which were loaded to area I and area II in second simulation, also get the number of particle which were loaded from drum envelope range; Output velocity respectively in X, Y, Z directions.

Figure 4: Flow chart of drum coal loading simulation with DEM

The statistical area of loaded particle was divides into area I and area II as shown in Fig.4. According to the coal loading process, some particles in area II were from drum loading performance, some were from the falling of particles in area I. The accumulating mass of particles which were loaded to area I and area II need to be statisticed in this paper, as well as the accumulating mass of particles which were loaded to area II through drum loading and the particles mean velocity in X, Y, Z direction in drum enclosing interval. The statistic on accumulating mass of particles was used to study the drum transportation performance and the particles distribution. The particles mean velocity in X, Y, Z direction in drum enclosing interval

Vol. 21 [2016], Bund. 01 168 was used for the study on the change of tangential velocity and axial velocity. The relationship between particles velocity and coal loading mechanism was explored with different coal loading methods. The results and parameters under different test condition were listed in Table.1.

Table 1: Comparison of simulation result with test result under different test condition No. Coal loading

mode Rotation

speed(r/min) Hauling

speed(m/min) Experiment

loading rate(%) Simulation

loading rate(%) Relative error(%)

1 Ejection 45 0.98 77.6 82.57 6.40 2 Ejection 70 0.98 78.6 81.89 4.19 3 Ejection 105 0.98 68.1 71.33 4.74 4 Pushing 45 0.95 66.77 62.19 -6.86 5 Pushing 70 0.99 61.83 57.59 -6.86 6 Pushing 105 1.01 56.69 40.28 -28.95

Based on the simulation test in Table.1, the velocity in X, Y and Z direction and accumulating mass of particles which were loaded to area I and area II were statistically analysed in the paper. The X, Y, Z direction velocities of particles in drum envelope range (simulation test 1,2 and 3) was shown in Fig.5. The X, Y, Z direction velocities of particles in simulation test 4, 5 and 6 was shown in Fig.6. Statistics results of mean velocity in X, Y, Z direction and accumulating mass of particles in six groups simulation were presented in Table.2, while the statistic lasted for 10 s.

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Figure 5: X, Y, Z direction velocities of particles in drum envelope range

(simulation test 1,2 and 3)

Figure 6: X, Y, Z direction velocities of particles in drum envelope

range(simulation test 4, 5 and 6)

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Table 2: Statistics results of six group simulation

Team No.

Mean velocity in X

direction (m/s)

Mean velocity in Y

direction (m/s)

Mean velocity in Z

direction (m/s)

Particle accumulating mass in area I

(kg)

Particle accumulating mass in area II

(kg)

Particle total mass (kg)

1 4.37E-02 -4.09E-02 1.16E-02 21.99 2.31 24.30 2 9.55E-02 -5.10E-02 4.77E-02 21.81 2.70 24.50 3 1.63E-01 -6.73E-02 9.11E-02 19.00 5.57 24.57 4 1.09E-02 -2.76E-02 -3.25E-02 16.56 2.37 18.94 5 1.72E-02 -3.81E-02 -4.01E-02 15.34 5.10 20.44 6 2.2E-02 -3.64E-02 -5.04E-02 10.73 4.29 15.02

DISCUSSION OF THE RESULTS Table.1 showed that the relative error between simulation results and test results of was

within 10% besides the 6th test. By analyzing the 6th test results, the large difference may be caused by two reasons. First, the force transfer time among coal particles was restricted by the large drum rotate speed; second, as the large particle diameter was set in the simulation, the pushing force had poor transmission in axial, which made particles thrown behind the drum easily. By correlating the 6th and 3th test, we found that the DEM simulation results were less influenced by rotation speed of coal loading with drum ejection. The simulation accuracy of coal loading with drum pushing decreased significantly when the drum rotation speed was large.The velocity in X, Y, Z direction increased with the increase of the drum rotation speed when coal loading with ejection in Fig.5. When coal loading with pushing, the particle velocity increased with the increase of drum rotation speed in X, Z direction and the trend was not exist in Y direction as shown in Fig.6. Analyzing Fig.5 and Fig.6 together, we could see that period of speed fluctuation was half of drum rotation. When the rotation speed was larger, the fluctuation extent would higher and cyclicity would more obviously. So the larger rotation speed, the more violent motion condition, we concluded. The particle velocity in Y direction was equivalent to drum axial velocity. As seen in Table 2, the mean axial velocity of drum was far smaller than the value which calculated according to the reference[28], which caused by two reasons. On the one hand, the drum envelope range was chosen as the statistic area in the paper, which included the particles that were not forced by vane into statistical analysis. On the other hand, the interaction between particles was neglected on theoretical study, so the theoretical computation result was larger than simulation result and real value.

When coal loading is with drum ejection, the change of coal particles velocity in Y direction with rotation speed can be seen from Table 2. Due to the statistic area, mean velocity coal particles in Y direction not increased according to the increase range of drum rotation speed. When the rotation speed was small, the drum fill rate was high. The ratio of particle number in the vane envelope range to that in the drum envelope range was larger, which made a larger mean velocity of all particles. With the increase of drum rotation speed, the vane fill rate decreased, and the ratio of particle number in the vane envelope range to that in the drum envelope range also decreased. Although particles in vane envelope range obtained large speed, the mean velocity in Y direction didn’t improve too much as the ratio of particle number in vane envelope range decreased. The centrifugal force of particle increased with the increase of drum rotation speed, which led the particle thrown to vane edges. So the axial velocity further decreased.

When coal load with drum ejection, the increase degree of mean velocity in X, Z direction shown in Table 2 was greater than drum rotation speed. While drum rotation speed was small, the

Vol. 21 [2016], Bund. 01 171 particle moved in Y direction concluded by the ratio of mean velocity in Y direction to that in X, Z direction when drum rotation speed was 45 r/min. The movement of particles was characterized by slipping on vane without obvious ejection phenomenon, and particles were less likely taken to the behind of drum, so that the mean velocity of particles in X, Z direction was smaller; With the increase of drum rotation speed, the ejection phenomenon were growing. The particles were taken to the behind area easily by drum and obtained the larger velocity, which made the mean velocity in X, Z direction increased exponentially.

Mean velocity of particles in Y direction didn’t increase with the increase of rotation speed of drum with pushing which can be seen in Table 2. When pushing mode was used, the movement of particles was caused by pushing force transmission of vane. A response time was demanded for transmitting force to particles, which was restricted by a larger drum rotation speed. For that reasons, the mean velocity of particles in Y direction decreased when rotation speed was larger. From the Table 2 we can see that the increase in mean velocity in X direction seems to be fairly over rotation speed of drum, but the changing rules was not followed by the mean velocity in Z direction. The main reason was that: when coal loading with ejection, the mean value of particles velocity in Z direction mainly depended on its falling velocity, and the vane action on particles’ Z direction mean velocity could be ignored; when the rotation speed was lower, the particle falling main caused by gravity acceleration; when the rotation speed was faster, the falling speed of coal particles would be accelerated by conical pick; all of contents mentioned above made the particle mean velocity in Z direction was changed as Table 2 shown.

From Table 2 we also can see that with the increase of drum rotation speed, the number of particles which were loaded to area I decreased, while that loaded to area II increased when coal loading with ejection. It mainly caused by ejection function, which made a part of particles thrown to the behind of drum and entered the statistics area II. The number of particles which transported to outside of coal wall increased with the increase of drum rotation speed under the simulation conditions according to Table 2.

CONCLUSIONS The research on particle movement during drum coal loading process indicated that: when the

rotation speed of coal loading with drum ejection was slow, average velocity of particles in axial direction was the largest among three directions and the movement of particles was characterized by slipping on vane; with the increasing of drum rotation speed, the increasing amplitude of average velocity in axial direction was smaller than that of rotation speed; Under the condition of coal loading with drum pushing, the average velocity in axial direction was not increase as the increasing of drum rotation speed since the transmission form of pushing force. Besides, the cutting depth was small under the simulation conditions, so accumulation quantities of particles outside the coal wall increased with the increasing of drum rotation speed.

ACKNOWLEDGEMENTS This work was supported by the Scientific Research Foundation of Shandong University of

Science and Technology for Recruited Talents(2015RCJJ024).

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