Research ArticleApplication of the Bionic Concept in Reducing the ComplexityNoise and Drag of the Mega High-Speed Train Based on ComputerSimulation Technologies

He-xuan Hu ,1,2 Bo Tang,2,3 and Ye Zhang 1

1College of Computer and Information, Hohai University, Nanjing 211100, China2Department of Electrical Engineering, Tibet Agricultural and Animal Husbandry College, Tibet 860000, China3College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China

Correspondence should be addressed to He-xuan Hu; hexuan_hu@hhu.edu.cn

Received 7 May 2018; Revised 4 July 2018; Accepted 15 July 2018; Published 1 August 2018

Academic Editor: Changzhi Wu

Copyright © 2018 He-xuan Hu 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.

Regarding the continuous development of high-speed trains and the increase of running speeds, the aerodynamic design of high-speed trains has become significantly important, while reduction of drag and noise comprises a significant challenge in order tooptimize aerodynamic design of high-speed trains. The design form factor of a high-speed train is highly influenced byaerodynamic aspects including aerodynamic drag, lift force, and noise. With the high-speed train as the object, the paper aimsto take bionic concept as the entry point, selecting the hummingbird as the bionic prototype and extracting bionic elements toestablish a bionic train model. Then, the finite volume method was used for numerical simulation and analysis of theaerodynamic performance and aerodynamic noise of the bionic high-speed train. Computational results prove that drag andnoise of the bionic head type were lower than those of the original train; drag of the head train of the bionic model was reducedby 2.21% in comparison with the original model, while the whole-train drag was reduced by 3.53%, indicating that dragreduction effects are available and implying that the bionic head type could reduce drag and noise. Noise sources of the bionictrain are mainly located at positions with easy airflow separation and violent turbulence motion. Large turbulence energy is inbogie areas and mainly exists at the leeward side of the bogie area. Obviously, the bogie area is the major noise source of thetrain. Aerodynamic noise of the bionic train in far-field comprises a wide-frequency range. Noises were concentrated within613Hz~3150Hz. When the bionic high-speed train ran at 350 km/h, through comparative analysis of total noise levels atobserved points of the high-speed train, it is found that this position with the maximum noise level was 25m away from thehead train nose tip, with the maximum value of 88.4 dB (A). When the bionic train ran at 600 km/h, the maximum soundpressure level at the longitudinal point was 99.7 dB (A) and the average noise level was 96.6 dB (A). When the running speedincreased from 350 km/h to 600 km/h, the maximum noise level increased by 11.3 dB (A) and the average noise level increasedby 11.6 dB (A). Computation results of aerodynamic noise at the point which is 7.5m away from the rail center show that themaximum aerodynamic noise level existed at the first-end bogie of the head train, while the noise level was larger at the positioncloser to the ground.

1. Introduction

In some sense, high-speed trains are one of the many repre-sentatives of innovative power of a nation. For example,high-speed trains under Mount Fuji in Japan have becomethe calling card of Japanese Shinkansen [1]. 700 series trainswith a unique shape have been called as “Platypus” and arewidely known in the society. After that, Shinkansen head

types adopted bionic elements of birds and fish. Heads ofGermany ICE trains are shaped like spheroids and mainlyadopt organic curves and faces. High-speed trains in Francehave tough and sharp shapes as well as bold coating, embody-ing romantic themes of France. In order to find designenlightenment and cater to people’s desire for nature, a lotof fields have applied a lot of natural elements. High-speedtrains have also started bionic modeling, while the most

HindawiComplexityVolume 2018, Article ID 3689178, 14 pageshttps://doi.org/10.1155/2018/3689178

typical benefit is the outstanding aerodynamic performance[2]. Therefore, it has been tried to adopt the animals headform properties in designing the high-speed train heads [3]as they have shape characteristics which can be recognizedquickly while their appearance is intimate and impressive.According to the evolution theory [4], in the evolutionof animals, species development has been towards increas-ing speed and consuming less energy. Perfect body struc-tures of animals have a better aerodynamic performanceover artificial traffic tools. Animals which have perfectbody structures perform quite well in aerodynamic perfor-mance, especially in aspects such as reduction of drag andenergy, saving of energy consumption, reduction of emission,and environmental-friendly effects. Through discussion andresearch of bionic design theories, the paper makes beneficialsupplementation for existing train shape design theories,summarizes excellent innovative design methods both athome and abroad, and further explores associations betweenhead type bionic design of high-speed trains and their aero-dynamic performance, expecting to provide reference fordesign of head types of high-speed trains.

Bionics is a discipline which has achieved very fastdevelopment in recent years [5]. Bionics is a comprehensivediscipline which aims to research special structures, perfor-mance, signal control and feedback, energy conversion, andother aspects of organic creatures, apply them into a tech-nical engineering system, improve existing technical engi-neering equipment, and create new technical engineeringsystems such as structural construction and automatedequipment. To be brief, it is a science which imitates crea-tures. A lot of experts have conducted different researchesabout the application of bionic elements in engineeringtechnologies such as animal bionics, plant bionics, humanbionics, and microorganism.

Based on different bionic perspectives of high-speedtrains, many scholars have conducted the followingresearches on the bionic design of engineering structures.As for the aircrafts, Combes and Daniel [6–8] experimentedhawk moth wings, finding that aerodynamic force onlybrought tiny influences on passive elastic deformation ofwings. As believed by Usherwood and Ellington [9], the lift-drag ratio of deformation wings of a traditional aircraft wasonly increased to a small range, but their effects in dynamicwing patting shall be reconsidered. Nguyen et al. [10] testedtwo artificial wings with shapes of horsefly and hawk moth,wherein the wing was rotated by the angle of 60°. Withinthe patting frequency of 6–12Hz, the optimum wing shapewas found. Chen et al. [11] researched drag reduction effectsduring pigeon flying; quantified morphological characteris-tics and geometrical information of wing feather rear edgeof the pigeon were quantified. Modeling was conducted tothe bionic wing shape model, while its aerodynamic charac-teristics were analyzed. It is found that the bionic wing modelcan reduce air drag with the maximum reduction range ofabout 9.1%. Based on a three-dimensional wing, Shi et al.[12] conducted waveform design of the front and rear edgesand researched drag reduction mechanism of the waveformthree-dimensional bionic wing structure with parameterssuch as flow field structure and boundary layers. Zhang

et al. [13] conducted analog simulation of fluid dynamic fea-tures of bionic flapping wings based on fluent, finding thatfluid dynamic force of bionic flapping wings showed linearcharacteristics under small angles of attack, but embodiednonlinear changing trends under large angles of attack. Basedon microcosmic rough surface waxiness of the nanoscale ofthe lotus leaf surface, Wang et al. [14] introduced principles,manufacture methods, and research statuses of bionic ice-proof materials. Tong et al. [15, 16] and Jin et al. [17]researched flapping of insects such as dragonflies and yellowjackets and also conducted flow field researches of C-typeand S-type starting vorticity and so forth of fish. With regardto automobiles, Bouchard et al. [18] believed that bionicdesign appears at two main stages of specific automobiledesign course, including the external inspiration sourcewhich associates “regular” and “irregular” activities. Tianet al. [19], enlightened by fish that uses center fins to generatedisturbance to fluids so as to enhance motion stability, addeddisturbance plates similar with center fins in functions on thecar tail part; aiming at the drag increase and on this basis, aribbed bionic functional surface was added on the surfaceof the automobile and the automobile rear window. Numer-ical computation results show that adhesive force of the rearwheel was enhanced; handling stability of the car wasenhanced; tail airflows were teased effectively; airflow separa-tion was delayed; the drag decrease rate reached 4.938%.Song et al. [20] applied the bionic pit slot technical structureon the automobile surface to control the boundary layer torealize scattering decrease, so that loss of turbulent kineticenergy can be reduced. As for trains, Lee and Kim [21] con-ducted optimization analysis of nose tip of a train andobtained a nose tip shape with better aerodynamic perfor-mance. Hargroves and Smith [22] introduced streamlines ofJapanese 500 series Shinkansen trains for bionic design ofkingfisher bills. To reduce aerodynamic drag of high-speedtrains, Du et al. [23] took the shark surface as the bionicobject, established the geometric profile of a bionic non-smooth groove, and researched drag reduction effects of thebionic nonsmooth grooves, finding that the drag reductionrate could reach over 6%. To reduce aerodynamic noise ofhigh-speed trains, Wang et al. [24, 25] designed the Kochsnowflake surface texture and the rhombus surface textureon the carriage of a train, finding that noise was reducedobviously. In combination with the bionic shape, Xu et al.[26, 27] looked into industrial design of high-speed trainsfrom man-machine engineering and emotionalized design.Yi et al. [28] analyzed bionic trains of Malaysian high-speedtrains inspired from Malaysian tigers and summarized char-acteristics of successful design of form bionics. Wang W. andWang Z. [29] analyzed practice and appearance designmethods of Korean high-speed rails from 4 aspects such astrain aerodynamics, symbol design, fusion and coexistenceof national cultures, and bionic design. Shi et al. [12] appliedthe owl wing front-edge sawtooth structure in cylindrical rodsurfaces for bionic design, researched its noise reduction per-formance, and explored noise reduction effects brought bythe application of the surface bionic structure in high-speedtrain pantographs. Qi [1] selected a lot of bionic prototypes,conducted three-dimensional transformation of train head

2 Complexity

types, applied Chinese sturgeon elements in train shapedesign, and computed the aerodynamic drag coefficient of itunder the running speed of 350 km/h, but failed to analyzethe reasons for drag decrease.

Based on theories and methods of CFD (computationalfluid dynamics), the paper applies the computational fluidsoftware FLUENT for the numerical simulation. Mainresearch contents are as follows: animals with high speedsin the nature were extracted; feature control lines wereextracted; design requirements such as high-speed trainlimits were considered; CAD software was used to simulatea high-speed train bionic geometric model. Based on aerody-namic theories of vehicles [30], the existing high-speed trainCRH was taken as the reference object to set up an aerody-namic computation model of the high-speed train bionicmodel. Based on Lighthill acoustic analog theories, the aero-dynamic noise model of bionic model was established. TheFW-H equation [31] was used to solve propagation charac-teristics of acoustic fields. Based on drag characteristics, liftforce characteristics, aerodynamic pressure distribution,aerodynamic noise characteristics, and other aspects oftrains, bionic elements of the train bionic model were weak-ened; engineering improvements were realized, so engineer-ing requirements for shape technologies, running, and soforth could be reached.

2. Mathematical Model of High-Speed TrainsBased on the Bionic Concept

Mathematical method of the aerodynamic performance ofhigh-speed trains involves three-dimensional, incompress-ible, viscous, and non-fixed-length turbulence flow fields aswell as the controllable differential equation with the formof Reynolds-averaged Navier-Stokes equations (RANS) [32,33]. In other words, the standard k − ε model is as follows.

(i) Equation of continuity:

dρdt

+ ∂ ρu∂x

+ ∂ ρv∂y

+ ∂ ρw∂z

= 0 1

(ii) Momentum conservation equation:

∂ ρu∂t

+ div ρu u = div μ ⋅ grad u −∂p∂x

+ SMx,

∂ ρv∂t

+ div ρv v = div μ ⋅ grad v −∂p∂y

+ SMy ,

∂ ρw∂t

+ div ρww = div μ ⋅ grad w −∂p∂z

+ SMz

2

(iii) Energy conservation equation:

∂ ρi∂t

+ div ρiu = div κ

cp+ μtσT

grad T +Φ

3

(iv) Turbulence energy equation:

∂ ρk∂t

+ div ρku = div μ + μtσk

grad k − ρε + μtPG

4

(v) Turbulence energy dissipation rate equation:

∂ ρε

∂t+ div ρεu = div μ + μt

σεgrad ε

− ρC2ε2

k+ μtC1

ε

kPG,

μt = ρCμ

k2

ε,

PG = 2 ∂u∂x

2+ ∂v

∂y

2+ ∂w

∂z

2

+ ∂u∂y

+ ∂v∂x

2+ ∂u

∂z+ ∂w

∂x

2

+ ∂v∂z

+ ∂w∂y

2+ λ div u ,

5

where u, v, and w are components of flow rates incoordinate directions of x, y, and z; ρ is the fluid vol-ume density, constant is used as for the incompress-ible equation; μ is dynamic viscosity density of fluid;μt is the turbulence viscosity; k is the turbulencekinetic energy; ε is the dissipation rate of turbulencekinetic energy; T is the fluid temperature; κ the isthermal conductivity of air; cp is specific heat of airmass at constant pressure; C1, C2, Cμ, σk, and σεare constant empirical values, which are 1.44, 1.92,0.09, 1.0, and 1.3, respectively; Φ is the dissipationfunction; and SMx, SMy, and SMz are source items ofmomentum equations in directions of x, y, and z.

SMx =∂∂x

μ∂u∂x

+ ∂∂y

μ∂v∂x

+ ∂∂z

μ∂w∂x

+ ∂∂x

λ div u ,

SMy =∂∂x

μ∂u∂y

+ ∂∂y

μ∂v∂y

+ ∂∂z

μ∂w∂y

+ ∂∂y

λ div u ,

SMz =∂∂x

μ∂u∂z

+ ∂∂y

μ∂v∂z

+ ∂∂z

μ∂w∂z

+ ∂∂z

λ div u

6

In the RNG k − εmodel [34, 35] (renormalization group,RNG), influences of small scales are embodied by the viscos-ity item after large-scale motion and amendment, so small-scale motion can be systematically removed from the control

3Complexity

equation. Through amendment of the turbulence viscosity,rotation and rotation flowing in average flowing are takeninto account. The time-average strain rate in main streamscan be reflected. Obviously, the RNG k − ε model can betterdeal with flowing with high strain rates and large flow linebending degrees. In comparison with the standard k − εmodel, it can get converged more easily in aerodynamic per-formance computation of high-speed trains. Hence, it iswidely applied in engineering practice. Therefore, the RNGk − ε turbulence model is selected in computing aerodynamicperformance of the train.

3. Numerical Model of High-Speed Trains Basedon the Bionic Concept

3.1. Bionic Design Science. Various creatures in the naturehave peculiar skills, which attract human to explore theirsecrets. Based on observation, thinking as well as rich imagi-nation, and creativity, people use various methods and tech-nologies to imitate and upgrade special skills and advantagesof creatures, do creative work, and create more rational andoutstanding tools. Bionic design science takes some elements

or individuals existing in the nature as research objects,applies these elements during design in a selective and pur-poseful manner, makes combination with engineering appli-cation, and provides diversified new methods for engineeringdesign. Research types of bionic design include form bionics,function bionics, color bionics, and structure bionics.

As shown in Figure 1(a), when optimization of automo-bile shape and intercavity interaction needs to be consideredduring engineering design, analysis and research can be con-ducted to some creative structures which have weak interac-tions with fluids, so a low-drag profile can be obtained. Inaddition, bionics can be conducted with some structures ofobjects. Figure 1(b) shows the design of a nylon hook andloop fastener realized by interactions between plants andexternal environment. As shown in Figure 1(c), engineeringapplication of wings which imitate dragonfly wings was real-ized. Research results show that wings imitating dragonflywings have advantages such as high structural strength, lightmass, and good aerodynamic characteristics, which can helpto enhance flight performance of planes significantly.

3.2. Selection of Excellent Bionic Prototypes. High-speed trainis considered as a form of transformation vehicles with a highrunning speed. During its head type design, animals withhigh speeds in the nature will be associated. From the per-spective of aerodynamics, birds flying in air and fish in waterhave realized survival of the fittest during hundreds of mil-lions of years and take a place in the biologic chain becauseof their nice head streamline. There are a lot of excellent spe-cies. Due to the limit of time and vigor, the paper selects arepresentative animal for further research and analysis.

Among all the animals, hummingbird (as shown inFigure 2) has the nice shape and magnificent colors. Withthe smallest volume, it is light, rapid, and agile. Magnificentfeather flickers with the gloss of metal, as bright as diamond.Nectar is its favorite. The long and thin beak extends deepinto a flower, but will not bring any harm to the flower, indi-cating that hummingbird has very good flying performanceand a smooth beak shape. They are distributed in the hottestareas of America and behave actively between two tropics,just like the followers of sun. In American myths, it is deemedas the god of sun, which brings kindling to the world.

3.3. Three-Dimensional Transformation of Bionic Prototypeand Referential Train Type. In order to study advantagesand mechanisms of bionic design in drag reduction, theCRH3 train was taken as a referential model (see Figure 3).

(a) Engineering bionics of dolphin [36]

(b) Engineering bionics of xanthium plant [36]

(c) Engineering bionics of dragonfly wings [37]

Figure 1: Real examples of engineering bionic design.

Figure 2: Hummingbirds as the selected excellent bionicprototypes.

4 Complexity

Three-dimensional construction of form of the humming-bird was conducted to ensure normalizing. In order to keepform characteristics of the animal to the hilt, structuressuch as cab window, diversion trench, top and bottomstructures of the train, and intertrain joints are not consid-ered temporarily. In this way, construction made by thebionic prototype to aerodynamic reduction in drag and noisecan be researched more purely.

From the complicated three-dimensional structure, char-acteristic lines which have the simplest structure and containthe most form connotations are extracted. Different specieshave different shapes, so their characteristic lines are differ-ent. Head feature lines of the hummingbird are used todesign streamline parts of the train head, so the form bionicsense of train head can be embodied. With stronger bionicelements, characteristic lines can generate stronger bionicsense. At first, minor characteristics are neglected throughobservation of main appearance characteristics of the animal.Secondly, main appearance characteristics extracted at thefirst step are simplified in combination with form structurecharacteristics of the train, such as longitudinal control lineof head part, horizontal control line of head part, andcross-section outline line of the train body, while simplifiedresults are applied to form design of streamline parts of thetrain head part, as shown in Figure 4.

Head type of hummingbirds was taken as the researchobject. Original head type for hummingbird bionic designwas established, as shown in Figure 5. It was simplified tobe similar with CRH high-speed train. Structural controllines and faces were optimized for mesh division and

computation. Main reference indexes include cross-sectional area and streamline length. After simplification,the mid train is 25m long and the tail train is 25m long.Three-train marshalling was adopted. The whole train is75m long, 3.64m high, and 3.26m wide, wherein the stream-line length was about 7.45m.

3.4. Engineering Application of Bionic Head Type.Appearance of the hummingbird bionic head type isnot flat. Aerodynamic pressures are distributed in a greatlyuneven manner. Obvious areas of positive pressures and neg-ative pressures appear. It bears huge positive and negativepressures, which may bring adverse influences to intensityand aerodynamic performance of trains. Hence, subse-quent researches will conduct engineering improvementsof streamline parts.

Engineering improvements of the bionic head typesmainly focus on two aspects: streamline shape and streamlinelength size. Head elements of different animals have differentcharacteristics. It is necessary to discover different bionicelements, so as to obtain application rules of bionic elementsin the design of the high-speed train head shape.

A lot of shape elements of the animal are kept during ini-tial design of bionic design. In engineering, the streamline isnot applicable, while shape technologies are difficult. In orderto satisfy requirements for engineering and manufacturetechnologies, engineering of the speed level 350 km/h wasconducted to the bionic design train. Length, width, andheight of the streamline part can refer to the CRH3 high-speed train. Bionic elements were kept as much as possible.The unsmooth degrees were amended, and its aerodynamicperformance was researched. During actual running, influ-ences brought by bogies to flow fields during train runningcan be neglected. Bogie areas can be considered during engi-neering, so practical situations can be approached. Theengineering-oriented application model is shown in Figure 6.

3.5. Numerical Solution Domain of Bionic Head Type inEngineering Application. Computational domain of thebionic train with the bionic head type is shown in Figure 7.The length L = 75m was taken as the standard. Hence, thecomputational domain is 4L long, L wide, and 0 5L high.The distance between head train nose tip and the inflowingentrance is L. The distance between the tail train nose tipand the outflow exit is 2L. The distance between the trainand the track ground is 0.3m. The front cross section ABCD

Figure 3: The referential CRH3 high-speed train.

Figure 4: Streamline head type of the hummingbird type.

Figure 5: Bionic head type of high-speed trains based onhummingbirds.

5Complexity

of the high-speed train was the entrance boundary and wasset as the speed entrance condition, wherein the speed was350 km/h (97.2222m/s) during the numerical computation.The rear cross section EFGH of the tail train of the high-speed train was the exit boundary and set as the pressurecondition with the size of one standard atmospheric pres-sure. Cross section BFGC right above the high-speed train,the left cross section CGHD, and the right cross sectionAEFB were set as symmetric boundary conditions. Surfaceof the bionic train was set as the fixed boundary, belongingto the no-slippage wall face boundary condition. To simu-late ground effects, the ground AEHD was set as the slip-page ground, wherein its slippage speed was equal to thetrain running speed.

The tool ICEM CFD was used to divide meshes. Mesheswith maximum outfield size of 1500mm, the maximummesh of 60mm on the train surface, and the maximum meshof 30mm on the bogie surface as well as other nonstructuralmeshes were extracted. Triangular meshes were adopted onthe train body and bogie surface. Sizes of three-dimensionalmeshes were amplified according to proportional factors.Hexahedral meshes were adopted at positions far from thetrain body, and pentahedron pyramid meshes were adoptedat transition parts from the tetrahedral meshes to hexahe-dral meshes. Local mesh densifying was conducted at partswith large changes of surface curvature at the streamlinehead type.

In order to eliminate influences of mesh density on com-putational results, three sets of meshes were selected for inde-pendence tests. Computation results of three sets of meshes

are shown in Table 1. Definitions of drag coefficient Cd andlift force coefficient Cl are

Cd =Fd

1/2ρv2S , 7

Cl =F l

1/2ρν2S , 8

where Fd and F l denote aerodynamic drag and lift forceborne by the high-speed train, ρ denotes air density, vdenotes the running speed of the high-speed train, and Sdenotes the maximum cross-sectional area of the high-speed train.

It is shown in Table 1: in comparison with the first set ofmeshes, the computed drag coefficient variation rate of thesecond set of meshes was 0.44%, while the variation rate oflift force of the tail train was 3.73%; in comparison with thesecond set of meshes, the computed drag coefficient variationrate of the third set of meshes was 0.12%, while the variationrate of the lift force coefficient of the tail train was 0.78%. Incomparison with the second set of meshes, variation rate ofcomputation results of the third set of meshes, as comparedwith the second set of meshes, was within 1%. Hence, the sizeof the second set of meshes was finally applied in mesh divi-sion. Surface meshes of streamline areas of the head train areshown in Figure 8. Total number of corresponding mesheswas about 33.12 million.

4. Aerodynamic Performance Analysis of High-Speed Trains Based on the Bionic Concept

4.1. Flow Field Characteristics of Bionic Trains. Noise sourceof the bionic train is the dipole noise. The dipole soundsource on the train surface depends on pulsation pressure

Figure 6: Engineering application head type of the hummingbirdbionic design.

Body

CB

A

D

E

F

H

G

Figure 7: Aerodynamic noise computation domain of high-speedtrains.

Table 1: Computation results of three sets of meshes.

MeshQuantity of meshes

(1 million)Drag coefficientCd of whole train

Lift forcecoefficient oftail train Cl

1 27.78 0.1792 0.0359

2 33.12 0.1866 0.0382

3 36.82 0.1856 0.0373

Figure 8: Meshes of head train of high-speed trains.

6 Complexity

of the train surface. In other words, the size of the pulsationpressure on the train surface can reflect far-field noise radia-tion on the sound production face. According to three con-trol equations of flow fields, turbulence energy equation,and turbulence dissipation rate equation, it is found that asfor the size of the pulsation pressure on the train body sur-face, the turbulence energy k can be used to assess distribu-tion characteristics of train surface noise. Expression of the

turbulence energy k is k = 1/2 u2 + v

2 +w2.

Figure 9 shows distribution contours of surface turbu-lence energy of the whole train and the head. Figure 10 showsturbulence energy distribution contours on the head trainsurface. It is shown in Figure 9 that high turbulence energywas at the head nose tip and the rear area of the tail nosetip. Fluid separation and aggregation took place alternately.Hence, it is obvious that the head is the major noise sourceof the bionic train. It is shown in Figure 10 that turbulenceenergy also existed in bogie areas and mainly existed at lee-ward sides of the bogie areas. Hence, we can find that thebogie area is also the major noise source of the bionic train.Therefore, sound source areas of the high-speed train existedat positions with easy airflow separation and violent turbu-lence motion.

Figure 11 shows the pressure contour of the bionic trainsurface running at speed of 350 km/h. It is shown inFigure 11(b) that the pressure on the nose tip of the headtrain was the maximum, with the size of 5669Pa. The maxi-mum negative pressure was located at the pilot, with the sizeof 10,636 Pa. The speed at the stagnation point of the headtrain nose tip was 0, and airflows got diverged at the headnose tip, so the maximum positive pressure appeared at thehead nose tip. Due to flow choking at the windward side ofthe head train pilot, airflow separation appeared at the lee-ward side of the head train pilot and airflows quickly flowinto the bogie area, so the maximum negative pressureappeared at the leeward side of the head train pilot. It isshown in Figure 11(c) that the pressure on the cab windowof the tail train was the maximum, with the size of 2146Pa,which was attributed to the structure at the tail train window.The maximum negative pressure was located at the skirtboard of the tail train bogie, with the size of 6900Pa.

4.2. Basic Aerodynamic Characteristics of Bionic Trains.Figure 12 shows the aerodynamic drag distribution contourof the bionic model, wherein the bionic high-speed trainran at 350 km/h. It is shown in Figure 12 that the sequence

5

25

45

6575

15

35

55

(a) Whole train

5

25

45

65

75

15

35

55

(b) Head train

5

25

45

6575

15

35

55

(c) Tail train

Figure 9: Distribution of turbulence kinetic energy around high-speed trains.

7Complexity

of the pressure difference of each train body (from large tosmall) is tail train, head train, and mid train; the sequenceof the pressure difference drag of each train body (from largeto small) is tail train, head train, and mid train, with values of4821N, 3637N, and 931N, respectively; the sequence ofviscosity drag of each train body (from large to small) is headtrain, mid train, and tail train with values of 3095N, 2457N,and 2138N, respectively; the drag of each train body (fromlarge to small) is tail train, head train, and mid train, withvalues of 6960N, 6733N, and 3389N, respectively; with dragof the bogie was considered, the sequence of total drag ofeach train body obtained (from large to small) is head train,tail train, and mid train, with values of 11,282N, 8353N,and 5439N, respectively.

Meanwhile, basic aerodynamic coefficients were com-puted. Using (7) and (8), the drag coefficients of the headtrain, mid train, and tail train were 0.19, 0.09, and 0.15,

respectively; the lift force coefficients of the head train,mid train, and tail train were −0.10, 0.01, and 0.17, respec-tively. Obviously, the head train bore downward lift force;the tail train bore upward lift force; the mid train nearlybore no lift force.

Meanwhile, through comparison of aerodynamic drag ofthe CRH3 high-speed train, we can find that, as for the bionictrain mode in the paper, the head train drag was reduced by2.21%; drag force of the whole train was reduced by 3.53%.Drag reduction effects were obvious.

5. Analysis of Aerodynamic Noise of High-SpeedTrain Based on Bionic Design

5.1. Arrangement of Observed Points. Noise of high-speedtrains along lines is one of the high-speed train noise prob-lems attracting most attention from people. Far-field lateral

Turbulent Kinetic energy

5

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(a) Whole train

Turbulent Kinetic energy

5

25

45

6575

15

35

55

(b) Head train

Turbulent Kinetic energy

5

25

45

65

75

15

35

55

(c) Tail train

Figure 10: Distribution of turbulence kinetic energy of the bionic train body.

8 Complexity

noise can form strong noise pollution along the line. In orderto research noise characteristics of the bionic train in far-field, 76 noise monitoring points were uniformly arrangedalong the longitudinal direction (X direction) of the train atpositions which were 3.5m higher above the track and 25maway from the track according to international standardsfor testing noise of bionic trains ISO3095-2005 [38],wherein the distance between adjacent longitudinal monitor-ing points was 1m. At positions which were 3.5m higherabove the track and 7.5m away from the track center, 8 noisemonitoring points were arranged along the longitudinaldirection of the bionic train, wherein 1 noise monitoringpoint was arranged at the head nose tip, the first-end bogie,the second-end bogie of the bionic head train, the first-endbogie of the bionic mid train, the second-end bogie of the

bionic mid train, the second-end bogie of the bionic tail train,the first-end bogie of the bionic tail train, and the tail nose tip(number of monitoring points: y11, y12, y13, y14, y15, y16,y17, and y18). At positions which were 1.2m higher abovethe track and 7.5m away from the center line of the track, 8noise monitoring points were arranged along the longitudi-nal direction of the train, wherein 1 noise monitoring pointwas arranged at the head nose tip of the bionic train, thefirst-end bogie of the bionic head train, the second-end bogieof the bionic head train, the first-end bogie of the bionicmid train, the second end bogie of the bionic mid train,the second-end bogie of the bionic tail train, the first-end bogie of the bionic tail train, and the tail nose tip ofthe bionic train (number of monitoring points: y21, y22,y23, y24, y25, y26, y27, and y28). Layout of noise bearing

Pressure (Pa)

−10636

−6560

−2483

1592

5669

(a) Whole train

Pressure (Pa)

−10636

−6560

−2483

1592

5669

(b) Head train

Pressure (Pa)

−6900

−4638

−2376

−115

2146

(c) Tail train

Figure 11: Pressure distribution on the surface of bionic trains.

9Complexity

points of the bionic train and number of noise bearingpoints are shown in Figure 13.

5.2. Distribution of Far-Field Noises for Bionic Trains.Figure 14 shows an A-weighting sound pressure level curveof longitudinal monitoring points during running of thebionic train model under 350 km/h, wherein the monitoringpoints were 25m away from the track center line and 3.5mhigher above the track face.

It is shown in Figure 14 that distribution of longitudinalaerodynamic noise pressure levels of the high-speed traintended to decrease, wherein the noise bearing point in thefirst-end bogie area of the head train had the largest soundpressure level which reached the maximum value. Totalsound pressure levels of the second-end bogie area of thehead train, the first-end bogie area of the mid train, thesecond-end bogie area of the mid train, the second-end bogiearea of the tail train, and the first-end bogie area of the tailtrain reached local maximum values. When the nose tip ofthe head train conducted transition to x = 7m, the noise levelin far-field increased rapidly with the maximum increment of4.9 dB (A); after that, noise pressure levels of the whole traingradually decreased, while when the nose tip of the head trainmade transition to x = 7m, the far-field noise pressure levelreached the maximum value at noise monitoring points ofthe whole train, namely, 88.4 dB (A); when x = 11m, thefar-field noise pressure level reached a large value of the noisemonitoring point of the whole train, namely, 88.1 dB (A); atstreamline parts of the tail train, the noise pressure level gotattenuated rapidly with the maximum attenuation value of8.9 dB (A). The total noise pressure levels reached locallylarge values near the second-end bogie of the head train,the first-end bogie of the mid train, the second-end bogieof the mid train, the second-end bogie, and the first-endbogie of the bionic tail train.

Figure 15 shows a comparative distribution diagram ofA-weighting sound pressure levels of longitudinal monitor-ing points along the longitudinal direction of the train duringrunning of the bionic model under different speeds (350 km/h and 600 km/h), wherein noise bearing points were 25m

away from the track center line and 3.5m higher above thetrack face.

It is shown in Figure 15 that noise levels of longitudinalnoise bearing points increased significantly with the increaseof train running speed. When the high-speed train ran at600 km/h, its maximum noise level at the longitudinal noisebearing points was 99.7dB (A) with the average sound pres-sure level of 96.6dB (A); when the running speed increasedfrom 350km/h to 600km/h, the maximum noise levelincreased by 11.3dB (A), while the average sound pressurelevel increased by 11.6dB (A). Meanwhile, it is shown inFigure 15 that, when the bionic model ran at different speeds,the total sound pressure levels of it at the first-end bogie of thehead train, the second-end bogie of the head train, the first-end bogie of the mid train, the second-end bogie of the midtrain, the second-end bogie of the tail train, and the first-endbogie area of the tail train reached locally maximum values.

Figure 16 shows the distribution of A-weighting soundpressure levels at 8 noise points which were arranged alongthe longitudinal direction, at positions which were 3.5mhigher above the track and 7.5m away from the track center(number of noise bearing points: y11, y12, y13, y14, y15, y16,y17, and y18). It is shown in Figure 16 that A-weighting noiselevels at the head nose tip of the bionic train, the first-endbogie of the head train, the second-end bogie of the headtrain, the first-end bogie of the mid train, the second-endbogie of the mid train, the second-end bogie of the tail train,the first-end bogie of the tail train, and the nose tip of the tailtrain were 87.7 dB (A), 92.9 dB (A), 89.8 dB (A), 90.5 dB (A),88.8 dB (A), 87.6 dB (A), 86.6 dB (A), and 81.7 dB (A).Increased amplitudes were 5.2 dB (A), −3.1 dB (A), 0.7 dB(A), −1.7 dB (A), −1.2 dB (A), −1.0 dB (A), and −4.9 dB (A).The sound pressure level of the noise monitoring point y12near the first-end bogie of the bionic head train reached themaximum value of 92.9 dB (A).

Figure 17 shows the distribution of A-weighting noiselevels of 8 noise points which were arranged along the longi-tudinal direction and located at positions 1.2m higher abovethe track and 7.5m away from the track center line (numberof monitoring points of noise bearing points: y21, y22, y23,y24, y25, y26, y27, and y28). It is shown in Figure 16 thatA-weighting noise levels at the head nose tip of the bionictrain, the first-end bogie of the bionic head train, thesecond-end bogie of the bionic head train, the first-end bogieof the mid train, the second-end bogie of the mid train, thesecond-end bogie of the tail train, the first-end bogie of thetail train, and the nose tip of the tail train were 88.4 dB (A),95.1 dB (A), 92.2 dB (A), 92.3 dB (A), 89.6 dB (A), 90.1 dB(A), 89.5 dB (A), and 82.4 dB (A). Increased amplitudeswere 6.7 dB (A), −2.9 dB (A), 0.1 dB (A), −2.7 dB (A),0.5 dB (A), −0.6 dB (A), and −7.1 dB (A). The sound pres-sure level at the noise monitoring point y22 near the first-end bogie of the bionic head train reached the maximumvalue of 95.1 dB (A).

Figure 18 shows a comparative diagram of A-weightingsound pressure levels of 16 noise bearing points which werearranged along the longitudinal direction of the train andlocated at positions 1.2m and 3.5m higher above the trackand 7.5 away from the track center. Through comparison

0

2000

4000

6000

8000

10000

12000

Pressure drag Viscous drag Drag Total drag

Dra

g (N

)

Head trainMid trainTail train

Figure 12: Aerodynamic drag of bionic model of high-speed trains.

10 Complexity

of Figure 18, we can find that the sound pressure levels ofnoise bearing points which were 1.2m higher were largerthan those of the noise bearing points which were 3.5mhigher. Obviously, sound pressure levels of the noise bear-ing points closer to the ground were larger. Sound pres-sure levels of 1.2m noise bearing points located at thehead nose tip of the bionic train, the first-end bogie ofthe head train, the second-end bogie of the head train,the first-end bogie of the mid train, the second-end bogieof the mid train, the second-end bogie of the tail train, thefirst-end bogie of the tail train, and the nose tip of the tailtrain were 0.7 dB (A), 2.2 dB (A), 2.4 dB (A), 1.8 dB (A),0.8 dB (A), 2.5 dB (A), 2.9 dB (A), and 0.7 dB (A) largerthan those of 3.5m noise bearing points. In conclusion,

during testing noise of the bionic train, noise monitoringpoints should be arranged at the y2 cross section, namely,at the first-end bogie of the head train.

Figure 19 shows a 1/3 octave comparison diagram of thebionic high-speed train at the monitoring point x7 (positionwith the maximum longitudinal sound pressure level). It isshown in Figure 19 that the noise of the bionic train was awide frequency spectrum in far-field, wherein its energywas mainly concentrated within 630Hz~3150Hz. With theincrease of train running speed, the far-field aerodynamicnoise energy moved to high frequencies.

x1

x76

y21

y11y12

y13y14

y15

y16

y17y18

y22

y23y24

y25y26

y27y28

Figure 13: Distribution of noise points of bionic trains in far-field.

76

78

80

82

84

86

88

90

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76

SPL

(dB)

(A)

Longitudinal distance (m)

Figure 14: Distribution of noise levels of longitudinal noisebearing points.

75

80

85

90

95

100

105

110

1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76

SPL

(dB)

(A)

Longitudinal distance (m)

350 km/h600 km/h

Figure 15: Comparison of sound pressure levels at longitudinalpoints with different speeds.

11Complexity

6. Conclusions

With the continuous development of high-speed trains andthe increase of running speeds, the aerodynamic problem oftrains has become increasingly significant. Appearance of atrain is closely associated with aerodynamic drag and aerody-namic noise of train running. In the paper, a bionic trainmodel was established by CAD software. Through simulation

with the FLUENT and numerical simulation, aerodynamicdrag reduction effect of the bionic train and influences ofaerodynamic noise on the train were analyzed. The followingconclusions are obtained:

(1) One animal with the high speed in the nature wasselected. Characteristic control lines were extracted.Design requirements such as high-speed train limitswere considered. CAD software was used to establisha bionic geometric model and a computation modelof the high-speed train. Correctness of the modelwas verified. The CFD software was used to computeaerodynamic performance and aerodynamic noisecharacteristics during open-line running of thebionic design train. As analyzed from the perspectiveof drag reduction, drag of the bionic design headtype was smaller than that of the CRH train; in com-parison with the CRH train, the head train drag ofthe bionic train model was reduced by 2.21%, andthe whole-train drag was reduced by 3.53%. Dragreduction effect was obvious. This result indicatesthat the bionic design head type has superiority indrag reduction.

(2) Sources of the bionic train are mainly located atpositions with easy airflow separation and violent

80

82

84

86

88

90

92

94

96

1 2 3 4 5 6 7 8

SPL

(dB)

(A)

Measure points

y11

92.9 dB(A)

y14

y12

y13y15

y16y17

y18

Figure 16: Distribution of noise levels of noise points which are7.5m far and 3.5m high.

7880828486889092949698

1 2 3 4 5 6 7 8

SPL

(dB)

(A)

Measure points

95.1 dB(A)

y28

y27y26y25y24y23

y22

y21

Figure 17: Noise levels of noise points which are 7.5m far and 1.2mhigh.

80828486889092949698

1 2 3 4 5 6 7 8

SPL

(dB)

(A)

Measure points

1.2 m3.5 m

0.7 dB(A)

2.2 dB(A)

2.4 dB(A)1.8 dB(A)

0.8 dB(A)2.5 dB(A)

2.9 dB(A)

0.7 dB(A)

Figure 18: Comparison of sound pressure levels of monitoringpoints 7.5m far.

30

40

50

60

70

80

90

100

0 1000 2000 3000 4000 5000

SPL

(dB)

(A)

Frequency (Hz)

(a) 350 km/h

30

40

50

60

70

80

90

100

0 1000 2000 3000 4000 5000

SPL

(dB)

(A)

Frequency (Hz)

(b) 600 km/h

Figure 19: Comparison of sound pressure levels under 1/3 octave.

12 Complexity

turbulence motion. Large turbulence energy exists inbogie areas and mainly exists at the leeward side ofbogie area. Obviously, the bogie area is the majorsource area of the bionic train.

(3) Noise of the bionic train model is a wide-frequencyspectrum in far-field, belonging to broadband noise.Energies are concentrated within 613Hz~3150Hz.

(4) When the high-speed train ran at 350 km/h, throughcomparative analysis of total noise levels at observedpoints of the high-speed train, it is found that themaximum noise level existed at the x7 noise pointwhich was 25m away from the head train nosetip, with the maximum value of 88.4 dB (A). Hence,in the subsequent experimental test, aerodynamicnoise points should be arranged at this position asmuch as possible.

(5) When the bionic train ran at 600 km/h, the maxi-mum noise level at the longitudinal noise bearingpoint was 99.7 dB (A), and the average noise levelwas 96.6 dB (A). When the running speed increasedfrom 350 km/h to 600 km/h, the maximum noiselevel increased by 11.3 dB (A) and the average noiselevel increased by 11.6 dB (A).

(6) Computation results of aerodynamic noise at themonitoring point which is 7.5m away from the railcenter show that the maximum aerodynamic noiselevel is at the first-end bogie part of the head train,while the noise level was larger at the position closerto the ground. It is suggested that noise bearingpoints shall be arranged at the first-end bogie of thehead train and at positions closer to the ground insubsequent experiments.

Data Availability

The data used to support the findings of this study areavailable from the corresponding author upon request.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This work is supported by National Natural Science Foun-dation of China (Grant no. 51667017) and Key ResearchProjects of Tibet Autonomous Region for Innovation andEntrepreneur (Grant no. Z2016D01G01/01).

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