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Hindawi Publishing CorporationAdvances in Materials Science and EngineeringVolume 2013, Article ID 254305, 9 pageshttp://dx.doi.org/10.1155/2013/254305

Research ArticleNumerical Analysis of Erosion Caused byBiomimetic Axial Fan Blade

Jun-Qiu Zhang,1 Zhi-Wu Han,1 Hui-Na Cao,1 Wei Yin,1

Shi-Chao Niu,1 and Hui-Yuan Wang2

1 Key Laboratory of Bionics Engineering of Ministry of Education, Jilin University, Changchun 130022, China2 College of Materials Science and Engineering, Jilin University, Changchun 130022, China

Correspondence should be addressed to Zhi-Wu Han; [email protected]

Received 29 September 2013; Accepted 27 November 2013

Academic Editor: S. Miyazaki

Copyright © 2013 Jun-Qiu Zhang et al.This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Damage caused by erosion has been reported in several industries for a wide range of situations. In the present work, a newmethodis presented to improve the erosion resistance of machine components by biomimetic method. A numerical investigation of solidparticle erosion in the standard and biomimetic configuration blade of axial fan is presented.The analysis consists in the applicationof the discrete phase model, for modeling the solid particles flow, and the Eulerian conservation equations to the continuousphase.The numerical study employs computational fluid dynamics (CFD) software, based on a finite volumemethod. User-definedfunction was used to define wear equation. Gas/solid flow axial fan was simulated to calculate the erosion rate of the particles onthe fan blades and comparatively analyzed the erosive wear of the smooth surface, the groove-shaped, and convex hull-shapedbiomimetic surface axial flow fan blade.The results show that the groove-shaped biomimetic blade antierosion ability is better thanthat of the other two fan blades.Thoroughly analyze of antierosionmechanism of the biomimetic blade frommany factors includingthe flow velocity contours and flow path lines, impact velocity, impact angle, particle trajectories, and the number of collisions.

1. Introduction

Wear is one of the main reasons for failures of mechanicalparts. [1, 2] Erosion is an attractive branch in the domainof wear. Solid particle erosion is a dynamic process thatoccurs in different machine-parts due to the impingement ofsolid particles [3]. Centrifugal and axial fan workingmediumcontains large amounts of solid particles, the particles impact-ing the surface of blade by very high speed and causingerosion of blade and housing; the erosion of blade is the mostserious, often appear blade fracture, runaway and othermajoraccidents. Hence, researches in material erosion includingmechanism, factors of erosion, and the optimal selection ofmaterials play a significant role in saving materials, reducingenergy consumption, and improving economic efficiency.Inevitably, research on erosion is attracting more and moreattention in the international academic circle [4–8]. It hasbeen concluded by previous investigators that general meth-ods used to reduce erosion are enhancing the wear resistance

of material surface by means of wear resistant materials orcoating material with better wear resistance [9–13].

Nature is a school for scientists and engineers; afterbillions of years of evolution, creatures in nature possessalmost perfect structures and functions [14, 15]. In nature,some animals, for example, scorpion, are living in the sandand other gas/solidmixed-media environment, which exhibitexcellent antierosion function under gas/solid mixed mediaenvironment [16]. Han et al. [17] showed that scorpionsthrough the adaptation of the living environment and theirown evolution, the formation of a special distribution of theconvex and groove on the back, which can change the state ofthe surface boundary layer flow, and hence, reduce erosion ofsurface. Figure 1 illustrates themorphology of desert scorpionand biomimetic modeling.

Many of the factors which control the rate of erosion,such as particle velocity or particle mass flow rate, particlediameter, impact angle, and particle distribution can bestudied at different flow conditions of the system. A lot of

2 Advances in Materials Science and Engineering

(e)

(d)(b)

(c)(a)

Figure 1: The dorsal surface of the scorpion: (a) scanned data using a laser scanner; (b) the groove of scorpion back; (c) the convex hull ofscorpion back; (d) bionic groove pattern; (e) bionic convex pattern.

practical examples may be found when a change in flowconditions has greatly increased or decreased erosion.

The experimental study on the dynamic behavior of solidparticles requires special equipment andmethodology to pur-sue this goal. Also, the erosion process is a complex problemto obtain a mathematical formula to account for some ofthe factors which control the rate of erosion of the blade.This paper presents a numerical study of the erosion processof biomimetic axial fan blade, applying computational fluiddynamics (CFD).

2. Description of Analysis

The numerical study of the erosion process applying CFDconsiders a mathematical model with Eulerian conservationequations in the continuous phase and a Lagrangian frame tosimulate a discrete second phase. The dispersion of particlesin the fluid phase can be predicted using a stochastic trackingmodel. This model includes the effect of instantaneousturbulent velocity fluctuations on the particle trajectories.

2.1. Governing Equations. The computational domain con-siders the mass conservation and momentum equations forincompressible flow in a 3D geometry in a steady state. Themass conservation is

∇ ⋅ 𝜌] = 𝑆𝑚, (1)

where ∇ is the operator nabla, 𝜌 is the density (kg/m3), ]is the velocity vector (m/s), and 𝑆

𝑚is the mass added to

the continuous phase from the dispersed second phase. Themomentum equation is

∇ ⋅ (𝜌]]) = −∇𝑝 + ∇ ⋅ 𝜏 + 𝐹, (2)

where 𝑝 is the pressure on the fluid micro unit (Pa), 𝜏 is thestress tensor, and 𝐹 are the forces that arise from interactionwith the dispersed phase. For turbulence, the numerical study

includes the standard 𝑘-𝜀 model [18], where the turbulentkinetic energy equation, 𝑘, is expressed by

𝜕 (𝜌𝜅𝑢𝑖)

𝜕𝑥𝑖

=𝜕

𝜕𝑥𝑗

[(𝜇 +𝜇𝑖

𝜎𝑘

)𝜕𝑘

𝜕𝑥𝑗

] + 𝐺𝑘− 𝜌𝜀, (3)

and the dissipation rate equation, 𝜀, is expressed by

𝜕 (𝜌𝜀𝑢𝑖)

𝜕𝑥𝑖

=𝜕

𝜕𝑥𝑗

[(𝜇 +𝜇𝑡

𝜎𝜀

)𝜕𝑘

𝜕𝑥𝑗

] + 𝐶1𝜀

𝜀

𝑘𝐺𝐾− 𝐶2𝜀𝜌𝜀2

𝑘,

(4)

where 𝑢𝑖is the velocity on the direction 𝑖 (m/s), 𝑥

𝑖is distance

coordinate on the direction 𝑖 (m), 𝑥𝑗is distance coordinate on

the direction 𝑗 (m), 𝜇 is molecular dynamic viscosity (kg/ms), 𝜇𝑖is molecular dynamic viscosity on the direction 𝑖 (kg/m

s), 𝐺𝑘represents the generation of turbulent kinetic energy

due the mean velocity gradients, 𝐶1𝜀

and 𝐶2𝜀

are constants(𝐶1𝜀

= 1.44, 𝐶2𝜀

= 1.92), and 𝜎𝑘, 𝜎𝜀are the turbulent Prandtl

numbers for 𝑘 and 𝜀 (𝜎𝑘= 1.0, 𝜎

𝜀= 1.3), respectively.

2.2. Discrete Phase Model (DPM). This model permits usto simulate a discrete second phase in a Lagrangian frameof reference, where the second phase consists of sphericalparticles dispersed in the continuous phase. The couplingbetween the phases and its impact on both the discrete phasetrajectories and the continuous phase flow is included. Theturbulent dispersion of particles ismodeled using a stochasticdiscrete-particle approach. This approach predicts the tur-bulent dispersion by integrating the trajectory equations forindividual particles, using the instantaneous fluid velocity.Theprediction of particle dispersionmakes use of the conceptof the integral time scale, 𝑇

𝐿, which describes the time spent

in turbulent motion along the particle path. This time scalecan be approximated in the standard 𝑘-𝜀model as

𝑇𝐿≈ 0.15

𝑘

𝜀. (5)

Advances in Materials Science and Engineering 3

Figure 2: The geometrized structure graph of axial fan blades.

The trajectory of a discrete phase particle can be predictedby integrating the force balance on the particle, which iswritten in a Lagrangian reference frame. This force balanceequates the particle inertia with the forces acting on theparticle:

𝑑𝑢𝑝

𝑑𝑡= 𝐹𝐷(𝑢 − 𝑢

𝑝) + 𝐹other, (6)

where 𝑢𝑝is the particle velocity (m/s), 𝑢 is the velocity (m/s),

𝐹𝐷is drag force (N), 𝐹

𝐷(𝑢 − 𝑢

𝑝) is the drag force per unit

particle mass, 𝐹other is the additional forces (N), and 𝐹𝐷 isdefined as

𝐹𝐷=

18𝜇

𝜌𝑑𝑑2𝑝

𝐶𝐷𝑅𝑒

24, (7)

where 𝐶𝐷

is the drag coefficient is applied for smoothspherical particles, 𝑅

𝑒is the relative Reynolds number, and

𝑑𝑝is the particle diameter (m).The additional forces,𝐹other, in

this case are compounded by the force required to acceleratethe fluid surrounding the particle, defined as

𝐹other =1

2

𝜌

𝜌𝑝

𝑑

𝑑𝑡(𝑢 − 𝑢

𝑝) , (8)

where 𝜌𝑝is the apparent density of the particles, which is

important when 𝜌 > 𝜌𝑝, and an additional force due to the

pressure gradient in the fluid is

𝐹other =𝜌

𝜌𝑝

𝑢𝑝

𝜕𝑢

𝜕𝑥. (9)

The relative Reynolds number, 𝑅𝑒, is defined as

𝑅𝑒=

𝜌𝑑𝑝(𝑢𝑝− 𝑢)

𝜇. (10)

To incorporate the effect of the discrete phase trajectorieson the continuum, it is important to compute the interphaseexchange of momentum from the particle to the continuousphase. This exchange is computed by examining the changein momentum of a particle as it passes through each controlvolume in the computational domain.

This momentum change is computed as

𝐹 = ∑(18𝜇

𝜌𝑑𝑑2𝑝

𝐶𝐷𝑅𝑒

24(𝑢𝑝− 𝑢) + 𝐹other)�̇�𝑝Δ𝑡. (11)

Finally, to evaluate the erosion rate at thewall of the blade,applying the discrete phase model, it is important to defineparameters such as the mass flow rate of the particle stream,�̇�𝑝, impact angle of the particle path with the wall face 𝛼,

function of the impact angle 𝑓(𝛼), and the area of the wallfacewhere the particle strikes the boundary𝐴 face.The erosionrate is defined as

𝑅erosion =

𝑁particle

∑

𝑝=1

�̇�𝑝𝐶 (𝑑𝑝) 𝑓 (𝛼) ]𝑏(])

𝐴 face, (12)

where 𝐶(𝑑𝑝) is a function of particle diameter, 𝛼 is the

impact angle of the particle path with the wall face, 𝑓(𝛼) isa function of impact angle, ] is the relative particle velocity,𝑏(]) is a function of relative particle velocity, and 𝐴 face isthe area of the cell face at the wall. In (12) the impactangle function was defined by a piece-linear profile and thediameter function and velocity exponent function are 1.8𝑒 −09 and 2.6, respectively [18].

2.3. Modeling of Axial Fan. Geometric construction andmeshing were performed with UG and GAMBIT. Bionicconfiguration created on the curved surface created by theprojection along the direction of the normal surface, surfacebias, and so forth. Figure 2 shows the geometrized structuregraph of axial fan blades.

2.4. Mesh Generation. Different mesh type and size wereused in each region, owing to the structure of each partof the axial fan, and the flow patterns are different. Longersegment structure of the inlet and outlet is simple, and theflow is relatively stable; hence, hexahedral grid was selectedin the two regions. Strong rotation in the blade regionalairflow, the flow is quite complex. Meanwhile, the structureof the leaves is more complex, especially the bionic blade.Therefore, selection of unstructured grid geometry structurestrong adaptability, and leaves of the surface of the grid areencrypted. Table 1 is the results of mesh generation.


Table 1: Each computational grid information of centrifugal fan.

Region of fan Lengthened segmentof air inletLengthened segment

of air outlet Smooth surfaceGroove surfacemorphology

Convex surfacemorphology

Grid type Hexahedral grid Hexahedral grid Tetrahedron gridrefinementTetrahedron grid

refinementTetrahedron grid

refinementCells 223816 498200 2000671 2089127 2070634

2.5. Calculation Model and Boundary Conditions. Pressure-inlet boundary condition was used in the entrance of fan.Pressure outlet boundary condition was used in the exit offan. The definition of turbulence parameters is based onturbulence intensity and hydraulic diameter.

Air flows in the tunnel with entrained solid particlesat 11.6m/s velocity. The injection type was set to surface.Solid particles with 1500 kg/m3 density were released fromthe inlet with an initial velocity of 11.6m/s assuming noslip between the particle and fluid. The particle diameterswere 20𝜇m, 50𝜇m, 100 𝜇m, 150𝜇m, and 300 𝜇m. And themass flow rate was 2 kg/s. Internal flow field of fan wasassumed to incompressible steady flow. RNG 𝑘-𝜀 model wasused as turbulence model. Standard wall function methodwas used near the wall. Solid wall boundary was assumedno slip, and wall roughness is 0.5. The interface boundarycondition was applied for interface of fluid region. SIMPLECalgorithm was used for velocity-pressure coupling. The dif-ferential equations were discretized by a first-order upwinddifferencing scheme. A convergence criterion of 10−3 for eachscaled residual component was specified for the relative errorbetween two successive iterations.

Open the two-phase coupling calculation in the settingspanel of discrete phase model. The boundary of reflect wasapplied for the wall and rebound model by using (13).Calculatingmodel of erosion rate by using (14), themodel forcoal ash particles impacting steel was achieved throughUDF:

𝑉𝑛2

𝑉𝑛1

= 1.0 − 0.4159𝛽1− 0.4994𝛽

2

1+ 0.292𝛽

3

1,

𝑉𝑡2

𝑉𝑡1

= 1.0 − 2.12𝛽1+ 3.0775𝛽

2

1− 1.1𝛽

3

1,

(13)

where 𝑉𝑛and 𝑉

𝑡are the normal component and tangential

component of particle collision surface speed, respectively,with the unit of m/s. The subscript 1, 2, respectively, denotesthe amount before and after the collision. 𝛽

1is the angle

between the particles speed and the surface tangent beforethe collision, and 𝛽

2is rebound angle of particles after the

collision, and the unit is rad.Experimental measurements reported by Hamed et al.

[19, 20] indicated that erosion of a target material wasfound to be dependent upon the particle impact velocity andits impingement angle. Experimental measurements wereobtained for coal ash particles impacting steel at differentimpacting velocities and impingement angles. The experi-mental data was used to establish the following empiricalequation for the erosionmass parameter,𝑀, which is defined

as the ratio of the eroded mass of the target material to themass of the impinging particles:

𝑀 = 𝐾1𝑅𝑤

2

𝑉2

1cos2𝛽

1(1 − 𝑅

2

𝑇) + 𝐾3(𝑉1sin𝛽1)4

,

𝑅𝑤= 1 + 𝐶

𝑘(𝐾12sin(90

𝛽0

𝛽1)) ,

𝑅𝑇= 1 − 0.0016𝑉

1sin𝛽1,

(14)

where 𝑉𝑃and 𝛽

𝑃are the impact velocity (m/s) and impinge-

ment angle (∘), respectively. 𝛽0is maximum erosion angle (∘),

𝑅𝑇is tangential recovery ratio.The following valueswere used

for the variables in (14) for 𝛽0

= 25∘ (angle of maximum

erosion):

𝐶𝑘= 1 𝛽

1≤ 2𝛽0

𝐶𝑘= 0 𝛽

1> 2𝛽0

(15)

with𝐾1,𝐾2, and𝐾

3material constants which are found to be

𝐾1= 0.5225 × 10

−5, 𝐾2= 0.266799, 𝐾

3= 0.549 × 10

−12, and𝛽0= 25∘.

3. Results and Discussion

3.1. Numerical Simulation Results. The simulation results ofthe erosion rate of the three kinds of blades are shown inthe form of histogram in Figure 3. It was observed that thebionic blades exhibited better erosion resistance than thesmooth surface blades.The groove surface blades showed thebest erosion resistance compared to the other two kinds ofblades. It is concluded that the best condition to improve thecomponents erosion resistance is using the groove surfacemorphology.

3.2. Gas-Phase Flow Analysis. Figures 4, 5, and 6 show theflow velocity contours and flow path lines of the surfaceregion (𝑋 = 0 cross-section) of the three types blades. Ascan be seen from the velocity contours, the flow velocities arehigher around the smooth surface than those of the convexsurface and the groove surface. Especially in the groovechannel, the flow velocity was significantly lower than thatof the smooth surface. Compared to the flow path lines, it isshown that the flow path lines on the smooth surface weresmooth. On the convex surface were changed to a certaindegree, it is indicated that the air flow was disturbed by theconvex hull. But in the groove channel, the groove surfacehas a great influence on the airflow. The air was rotating inthe groove channel, forming a stable low-speed reverse flowzone [16, 21].


0e + 00

1.14e − 05

2.28e − 05

3.42e − 05

4.56e − 05

5.69e − 05

6.83e − 05

7.97e − 05

9.11e − 05

1.02e − 04

1.14e − 04

1.25e − 04

1.37e − 04

1.48e − 04

1.59e − 04

1.71e − 04

1.82e − 04

1.94e − 04

2.05e − 04

2.16e − 04

2.28e − 04

Contours of DPM erosion rate (kg/m2·s) Nov 11, 2010ANSYS fluent 12.1 (3d, pbns, mgke)

X

Y

Z

(a)

X

Y

Z


0e + 00

1.21e − 05

2.42e − 05

3.63e − 05

4.84e − 05

6.05e − 05

7.26e − 05

8.46e − 05

9.67e − 05

1.09e − 04

1.21e − 04

1.33e − 04

1.45e − 04

1.57e − 04

1.69e − 04

1.81e − 04

1.93e − 04

2.06e − 04

2.18e − 04

2.3e − 04

2.42e − 04

(b)

X

Y

Z


0e + 00

1.72e − 05

3.43e − 05

5.15e − 05

6.87e − 05

8.58e − 05

1.03e − 04

1.2e − 04

1.37e − 04

1.55e − 04

1.72e − 04

1.89e − 04

2.06e − 04

2.23e − 04

2.4e − 04

2.58e − 04

2.75e − 04

2.92e − 04

3.03e − 04

3.26e − 04

3.42e − 04

(c)

Figure 3: Numerical simulation results of the erosion rate of three kinds of blades: (a) groove surface morphology; (b) convex surfacemorphology; (c) smooth surface.

Velo

city

(m/s

)

2468101214161820222426283032343638

Figure 4: Flow velocity contours and path lines of the surface region of smooth surface.

The special flow pattern in the groove has significantinfluence on the erosion resistance of groove surface. Therotating flow in the groove plays an “air cushion” effect. Onthe one hand, the grooves can enhance fluid turbulence,which lead to the change of the flow field around thegroove surface, and the particle motion pattern was changedsubsequently. Some of the particles will leave the surface

along with air flow without impact, and these particles wouldimpact the surface if the surface was smooth. Therefore, thenumber of particles impacting the surface was decreased. Onthe other hand, as a result of the decrease the flow velocityand the velocities of the particles in the two-phase flow weredecreased as well. The rotating flow in the groove can absorbparticle energy which is used for impacting, and the energy


Velo

city

(m/s

)

2468101214161820222426283032343638

Figure 5: Flow velocity contours and path lines of the surface region of convex surface.Ve

loci

ty (m

/s)

2468101214161820222426283032343638

Figure 6: Flow velocity contours and path lines of the surface region of groove surface.

used in impact was correspondingly reduced. These featuresall help to reduce the particle impact damage on the bladesurface and reduce erosion wear [21].

3.3. Particles Impact Velocity Analysis. The particle impactvelocity is an important impingement variable which influ-ences the erosion behavior of materials. The dependence oferosion rate (𝐸) on impact velocity (V) is expressed by thefollowing equation:

𝐸 = 𝑘𝑉𝑛

, (16)

where 𝑛 is velocity exponent and 𝑘 is a constant. The velocityexponent is usually in the range of 2-3 for ductile materials,while, for brittle materials, it can be much higher. Hence, it isclear that the erosion rate increases significantly with increasein the impact velocity.

In the present work, the particle impact velocity distribu-tions on the surface of the three types of blades were analyzed.The particle impact velocities were obtained by the FLUENTpostprocessing system. The impact velocities were recorded

in the interval value of 2 units. Figure 7 shows the impactvelocity distribution on the blade surface. For the smoothsurface, the impact velocities are concentrated in 30m/s. Forthe convex surface, the impact velocities are in the range of5–35m/s, and mainly distributed in the range of 25–30m/swith the probability of this velocity being greater than 80%.But for the groove surface, the impact velocities are mostlyconcentrated in several fixed values, such as 10m/s, 16m/s,and 30m/s. There is a certain probability of impact velocitiesin 10m/s and 16m/s. As a result, the particle impacts on thegroove surface were occurred at the lower impact velocitiescompared with the smooth and convex surfaces, which leadto lower erosion than that of the other two types of surfaces[16].

3.4. Particles Impact Angle Analysis. Particle impact anglehas an important effect on the erosion rate. The maximumerosion of ductile material occurs at angles between 20–30∘[17]. The probability of particle impact angle distributionon the blade surface is shown in Figure 8. On the smooth


0 5 10 15 20 25 30 350

0.2

0.4

0.6

0.8

1

Smooth bladeConvex bladeGroove blade

Prob

abili

ty

Impact velocity (m/s)

Figure 7: Particle-surface impact velocity distribution.

0 10 20 30 40 50 60 70 80 900

0.2

0.4

0.6

0.8

1

Smooth bladeConvex bladeGroove blade

Prob

abili

ty

Impact angle (deg)

Figure 8: Particle-surface impact angle distribution.

surface, all the impact angles were concentrated in 30∘. Onthe convex surface, the impact angles are distributed in therange of 0–90∘, andmore than 60% probability impact anglesare in the range of 25–30∘. On the other hand, for the groovesurface, most of the impact angles fall in the range of 50–65∘.Therefore, compared with the smooth and convex surfaces,the impacts on the groove surface occurred at the high impactangleswhich lead to lower erosion.This is another reasonwhythe groove surface exhibits more erosion resistance [16].

3.5. Analysis of Particle Trajectories and Collision Times.Figures 9, 10, and 11 are the trajectories of 10 particlesfrom the incident source under given simulation conditions.

Incident direction

Rebound direction

0e + 00

2.23e + 00

4.47e + 00

6.7e + 00

8.93e + 00

1.12e + 01

1.34e + 01

1.56e + 01

1.79e + 01

2.01e + 01

2.23e + 01

2.46e + 01

2.68e + 01

2.9e + 01

3.13e + 01

3.35e + 01

3.57e + 01

3.8e + 01

4.02e + 01

4.24e + 01

4.47e + 01

Particle velocity (m/s)

Figure 9: The trajectories of particle collision smooth surface.

Rebound direction

Incident

Particle velocity (m/s)

0e + 002.22e + 004.45e + 006.67e + 00

8.9e + 001.11e + 011.33e + 011.56e + 011.78e + 01

2e + 012.22e + 012.45e + 012.67e + 012.89e + 013.11e + 013.34e + 013.56e + 013.78e + 01

4e + 014.23e + 014.45e + 01

direction

Figure 10: The trajectories of particle collision convex surface.

The sampling analysis and statistic shows that the collisionnumber of 4240 particles from the incident source withsmooth blade, convex blade, and groove blade, respectively,291, 332, and 452. Obtained by calculating the numbers ofcollisions on the three-blade surfaces per unit area were 0.116,0.115, and 0.113/mm2.

It can be seen that the impact times of groove and convexsurfaces were lower than that of smooth surface, and thegroove surface showed the lowest impact times. Hence, thereduction of impact on the groove surface can lead to thedecrease of erosion wear to a certain degree.

4. Conclusions

In the present work continuous-discrete phase models areused to predict the erosion of the three kinds of blades.Conclusions are as follows.

The groove surface blades showed the best erosionresistance compared to other two kinds of blades. The flowvelocities are higher around the surface of smooth surfacethan those of the convex surface and the groove surface fromthe velocity contours.The groove surface has a great influence


0e + 002.34e + 004.66e + 007.03e + 009.37e + 001.17e + 011.41e + 011.64e + 011.87e + 012.11e + 012.34e + 012.58e + 012.81e + 013.04e + 013.28e + 013.51e + 013.75e + 013.98e + 014.22e + 014.45e + 014.68e + 01

Particle velocity (m/s)Incident

Rebound direction

direction

Figure 11: The trajectories of particle collision groove surface.

on the airflow. The particle impact velocity of biomimeticgroove axial fan blade is less than smooth blade and theconvex blade.The impacts on the biomimetic groove axial fanblade occurred at the high impact angles which are relativelyless susceptible to impact damage compared with the smoothand convex surfaces, while the surface smooth and convexhull-shaped biomimetic form of axial fan blades collisionoccurred in apt erosion low-angle region.The impact times ofgroove and convex surfaces were lower than those of smoothsurface, and the groove surface showed the lowest impacttimes.

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

Acknowledgment

This work was supported by the Natural Science Foun-dation of China (nos. 51175220 and 51205161), SpecializedResearch Fund for the Doctoral Program of Higher Edu-cation (nos. 20100061110023 and 20120061120051), ChinaPostdoctoral Science Foundation on the 51th Grant Program(2012M511345), the Projects of Cooperation and Innova-tion to National Potential Oil and Gas for Production andResearch (no. OSR-04-04), the Scientific and the Technologi-cal Development Project of Jilin Province (no. 20130522066),and Basic Scientific Research Expenses of Project of JilinUniversity (450060481176).

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