Roller-Integrated Acoustic Wave Detection Technique for ... - MDPI

applied sciences Article

Roller-Integrated Acoustic Wave Detection Technique for Rockfill Materials Qinglong Zhang

ID

, Tianyun Liu and Qingbin Li *

ID

Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China; [email protected] (Q.Z.); [email protected] (T.L.) * Correspondence: [email protected]; Tel.: +86-010-62771015 Received: 3 September 2017; Accepted: 26 October 2017; Published: 30 October 2017

Abstract: This paper proposes a roller-integrated acoustic wave detection technique for rockfill materials. This technique can be divided into two parts: theoretical analysis and technical implementation. Based on Lamb’s problem and an infinite baffle piston radiation acoustic field model, a relationship model between the sound compaction value (SCV) and the dry density of the natural gravel materials (NGM) was established, namely, A-model. During the modeling process, an innovative differential pulse excitation method (DPEM) was used to find the numerical solution of the vertical displacement of the soil surface under harmonic loads. In this research, a continuous compaction control acoustic wave detection system (CAWDS) was developed and utilized along with real-time kinematic global positioning systems (RTK-GPS). The SCV was adopted as a characterization index for the compaction quality of rockfill materials. A case study on a reservoir project in Luoyang, China indicated that the SCV is highly linearly correlated with the number of compaction times, dry density, and compactness of the NGM. This new technique demonstrated several advantages, such as higher accuracy, discreetness, convenience, and suitability for detecting the compactness of the NGM. This technique is an effective tool for compaction quality control of rockfill materials and has a great potential for further applications. Keywords: rockfill materials; sound compaction value; natural gravel materials; differential pulse excitation method; continuous compaction control acoustic wave detection system; real-time kinematic global positioning systems

1. Introduction Effective control of compaction quality is critical to ensure the safety of rockfill dams [1]. Many researchers have attempted to develop compaction detection techniques and methods for soil. Based on whether or not the detection equipment is in contact with the material, these detection techniques and methods can be classified into contact and non-contact techniques and methods. Contact techniques and methods include the water-filling method, the falling weight deflectometer (FWD), the lightweight deflectometer (LWD), the dynamic cone penetrometer (DCP), the California bearing ratio (CBR), the nuclear density gauge, the resistivity test method, and so on. Non-contact techniques and methods include the roller-integrated compaction monitoring (RICM) techniques, intelligent compaction (IC) techniques, the ground penetrating radar (GPR) techniques, the Rayleigh wave techniques, the near-infrared and microwave resonance sensing technique, and so on. Contact techniques and methods are utilized to detect the compactness of rockfill materials by measuring the density and moisture content of the materials. Krebs et al. [2] studied compaction control of highway materials using the sand cone method, which is time-consuming. In order to improve this disadvantage of the sand cone method, Rahman et al. [3] and Meehan et al. [4] further investigated compaction control of pavement layer materials and coarse-grained soil using the LWD, FWD, DCP,

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and soil stiffness gauge (SSG). Melbouci [5] and Zabilska-Adamska et al. [6] studied compaction control of recycled aggregate and cohesive soil and fly ash using the CBR test. Resende et al. [7] utilized the DCP to research quality control of mining tailing dams. Kongkitku et al. [8] developed the LWD for estimating the surface stiffness of lateritic soil. Subsequently, Umashankar et al. [9] utilized the LWD to study compaction control of pavement layers. To further simplify the operating process and improving efficiency, Swinford et al. [10] and White et al. [11] investigated soil compaction using the nuclear density gauge. Although contact techniques and methods have the advantages of high accuracy and wide application range, they also have obvious disadvantages of point sampling and destructive measurements, low efficiency, and higher requirements for operators. In order to avoid the disadvantages of contact techniques and methods, lots of researchers have developed non-contact techniques and methods. Thurner et al. [12] and Forssblad [13] stated that the vibration acceleration amplitude and harmonic amplitude were correlated with the soil density and the underlying stiffness. Anderegg et al. [14] extracted the stiffness of the soil based on the vibration acceleration and phase difference. With in-depth research, a relative measurement index value (RICMMV) based on RICM was proposed to determine the compactness of the soil [15–20]. RICMMV is defined in various ways, including compaction meter value (CMV) used by Geodynamic [15], Kb used by Ammann [16], machine drive power (MDP) used by Caterpillar [17–19], and OMEGA used by Bomag [20]. Furthermore, Rinehart et al. [21,22] pointed out that total harmonic distortion (THD) was a highly sensitive index for evaluating the compaction status of soil, and White et al. [18] introduced Evib as a vibration modulus. Related studies have demonstrated that these indexes are closely correlated to the stiffness or modulus of compacted materials, and the non-contact techniques and methods based on RICMMV can be used to detect the compactness and evaluate the compaction quality of soil. By combining AFC techniques, some researchers have developed IC for road compaction control, and IC is currently widely used in Europe, Japan, and the United States [23–25]. Moreover, wave techniques have been used to the detect compactness of subgrade [26,27]. However, the law and mechanism theory of wave propagation in various soils have been not yet been well studied. The wave techniques have larger detection errors and higher requirements for operators. For pavement, the GPR techniques can detect the moisture content and compactness of subgrade; however, the influence of the surface jet moisture on the GPR signal during the compaction is unknown [28]. Austin et al. [29] utilized the near-infrared and microwave resonance sensing technique to monitor a continuous roller compaction process; however, this technique has a complex application and data processing procedure. Based on practical applications, non-contact techniques and methods have the advantages of being nondestructive, fast, and efficient measurements, while the disadvantages are low accuracy, the inconvenience and complexity of interpreting the compaction situation, significant discreteness, more error in the results, and being easily influenced by material factors. In non-contact techniques and methods, CMV was often used to characterize the compactness of granular soils and evaluate the compaction quality [15,29]. Adam [20], Sandström [30], and Vennapusa et al. [31] indicated that CMV measurements must be interpreted in conjunction with the RMV measurements; this situation has caused inconvenience in the use of CMV [31]. Moreover, the research of White and Thompson [15] showed that CMV had greater discreteness and measurement errors; the discreteness of the CMV values increased with the increase of the particle sizes of the materials, and the measurement errors caused by discreteness made CMV unable to meet practical needs [15]. Based on the above problems, CMV was not suitable for rockfill materials with large particle sizes (>200 mm). Liu et al. [29] utilized RICM techniques to make a compaction quality assessment of earth–rock dam materials, the grain size of the material was less than 120 mm, the discreteness of CV values increased with the increase of particle size, and Liu’s method-based CV and regression model was not suitable for NGM (0.1~400 mm). The aim of this study was to propose a new compaction detection technique to solve problems with the current detection techniques.

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2. Methodologies The new compaction detection technique includes two aspects: theoretical analysis and technical implementation. In terms of the theoretical model, the interaction between the soil and the vibration wheel is considered as Lamb’s problem, namely, the propagation problem of vibrations over the surface of semi-infinite isotropic elastic solid, and the acoustic field generated by this interaction is regarded as the infinite baffle piston radiation acoustic field. The new technique is based on the vocal mechanism as follows: when the vibration wheel interacts with the soil, the soil is subjected to the vertical contact force and the horizontal friction. The combined action of the two forces makes the corresponding particles of the soil vibrate vertically and horizontally in a compound manner and simultaneously makes a sound. Meanwhile, the fluctuation caused by the vibration of the particles causes the density and pressure of the air medium at the interface between the soil and the gas to change, that is, the state of the air medium at the solid-air interface produces change. Thus, acoustic waves are generated at the interface and radiated in a certain form through the air medium. Considering the interaction form between the vibration wheel and the soil and its boundary condition, the acoustic wave radiation field formed at the solid-gas interface can be regarded as the piston-type radiation field on the infinite plate. Namely, when the vibration wave located in the solid medium surface propagates, a specific area located in the solid medium surface can be treated as the circular piston radiator on the infinite baffle; the piston vibrates in the vertical direction at speed u, and radiates acoustic waves to the semi-infinite space in front of the baffle. In terms of technical implementation, the detection principle is as follows: this acoustic wave detection technique includes detection and signal analysis. The detection equipment is installed on the vibratory roller and mainly contains the acoustic field microphone, the signal acquisition analyzer, the display, and the GPS receiver. When the filling layer is compacted by the roller, the time domain signal of the acoustic wave field formed near the contact surface of the vibratory wheel and the soil is received by the acoustic field microphone mounted on the outer frame of the vibration wheel, and then collected by the analyzer to form digital signals. The GPS receiver mounted on the roller simultaneously provides the spatial signal associated with the roller location. The signal acquisition analyzer performs the filtering and the spectrum analysis to the effective acoustic signal to obtain the second harmonic amplitude (SHA). According to the correlation between the SHA and the compactness or density of the rockfill material, a continuous compaction index is established after calibration. Combined with the spatial location information, a spatiotemporal compactness distribution map of the rolling region is presented on a roller-integrated display. In addition, combined with the compactness feedback module, it is easy to realize intelligent compaction by adjusting the mechanical parameters. 2.1. Theoretical Analysis 2.1.1. Lamb’s Problem The elastic fluctuation problem caused by dynamic line load or point load on the surface or interior of a semi-space is a type of problem with great significance in the fluctuation field of elastic solids. The original research can trace back to the classics of Lamb [32]. In the early 1930s, Cagniard developed a general method for solving Lamb problems, using this displacement field of the Fourier transform, with the inverse transformation obtained by using Laplace transform. After that, De Hoop [33] made further improvements. Reissner [34] has analyzed the flexible circular plate problem under a uniformly distributed load on an elastic semi-space, and the problem can be solved by the Rahm solution integration of point load problems. In 1953, Quinlan [35] and Sung [36] published two papers to expand Reissner’s solution by considering the influence of the pressure distribution on the circular contact area on the surface of the semi-space. For the dynamic response of saturated soil, Biot [37] first established the phenomenological theory of two-phased medium fluctuation problems. The establishment of the theory made it possible to study the vibration characteristics of the foundation on the saturated soil foundation in the real sense. Since Biot established the wave equation of saturated porous media

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study ofPaul Lamb’s when there were horizontal andout vertical forces on the surface of saturated in 1956, [38]problem and Philippacopoulos et al. [39] carried a thorough study of Lamb’s problem soil. Paul the viscous fluid in forces saturated soil, utilized the Hankel andthe Cagniard when thereignored were horizontal and vertical on the surface of saturated soil.transform Paul ignored viscous method, adopted the Helmholz decomposition proposed by Deresiewicz, and was the first to study fluid in saturated soil, utilized the Hankel transform and Cagniard method, adopted the Helmholz Lamb’s problemproposed in saturated semi-space. Wang et al.the [40], hypothesizing that viscosity included decomposition by Deresiewicz, and was first to study Lamb’s problemwas in saturated in the dynamic coefficient, that adopted the was integral transformation method to solve semi-space. Wangpermeability et al. [40], hypothesizing viscosity included in the dynamic permeability simultaneous coupled equations, avoided the introduction of potential functions, and gave the coefficient, adopted the integral transformation method to solve simultaneous coupled equations, integral the form solution ofofsaturated semi-space low-frequency harmonic concentrated avoided introduction potential elastic functions, and gaveunder the integral form solution of saturated elastic force. Cai [41] studied the steady response of axisymmetric soil under vertical load, and developed semi-space under low-frequency harmonic concentrated force. Cai [41] studied the steady response of the amplitudesoil curve of vertical surface load, displacement. On the of these fundamental solutions, the axisymmetric under and developed thebasis amplitude curve of surface displacement. dynamic interaction between saturated soil the anddynamic variousinteraction types of foundations has also On the basis of these fundamental solutions, between saturated soil been and extensively studied [42–44]. Lamb’s problem has been extensively studied internationally, and various types of foundations has also been extensively studied [42–44]. Lamb’s problem has been significant progress has been made.and The significant analysis methods ofhas such problems improving, extensively studied internationally, progress been made. are Theconstantly analysis methods of and the solution the problem is more refined. such problems aretoconstantly improving, and the solution to the problem is more refined. In this this paper, paper, the the interaction interaction between between the the soil soil and and the the vibratory vibratory wheel wheel was was considered considered as as Lamb’s Lamb’s In problemof of saturated saturatedsoil. soil. In In order order to to solve this problem, problem, based based on on the vertical displacement displacement solutions solutions problem in the case of normal concentrated load on the surface of the space, an innovative differential pulse in the case of normal concentrated load on the surface of the space, an innovative differential pulse excitation method method (DPEM) (DPEM) was was proposed proposed to to solve solve the the vertical vertical displacement displacement in in the the semi-space semi-space under under excitation simple harmonic harmonic loading. loading. The isotropic and homogeneous semi-space is shown in Figure 1, and and its its simple surface is the X–Y plane. surface is the X–Y plane. ( )

Figure 1. 1. Isotropic Isotropic and and homogeneous homogeneous semi-space. semi-space. Figure

The coordinate coordinateaxis axisz points points to the interior of the semi-space. There is a normal concentrated The to the interior of the semi-space. There is a normal concentrated load load of ( ) at the origin . Since the load is symmetrical to the axis, the problem of wave of QH (t) at the origin o. Since the load is symmetrical to the z axis, the problem of wave motion in motion in the infinite elastic is semi-space is axialBased symmetry. Based on coordinate a cylindrical coordinate the infinite elastic semi-space axial symmetry. on a cylindrical system (r, θ, z),system uz by (the, displacement , ), by the displacement potential and ( = 0) of the cylindrical coordinate system potential ϕ and χ(ψ = 0) of the cylindrical coordinate system symmetric situation symmetric situation are expressed as follows: are expressed as follows:   ∂ϕ 1 ∂ ∂χ . (1) uz = = − − r (1) ∂z r ∂r ∂r Based on on the the study study of of Lamb Lamb [32] [32] and and other other researchers researchers [35,38–40], [35,38–40], the the vertical vertical displacement displacement of of Based the surface is as follows: the surface is as follows:  0( < ⁄ )   0 (τ < c T /c(L )) ( ⁄ < < 1) − uz (r, 0,(t), 0, = ) =− π2QGr G1 (τ ) (c T /c L < τ < 1) ..   − −Q [ G[ (τ() + )+ G2 (τ()])](τ( >>11) ) 1 π 2 Gr

(2) (2)

After further investigation, Pekeris [45] obtained the analytic results of the integral by means of ( ), partial fraction decomposition of the integrand function of ( ) . Figure 2 shows the ( , 0, ) with the change of . alternative relation of the surface vertical displacement

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−

( , 0, )

After further investigation, Pekeris [45] obtained the analytic results of the integral by means of partial fraction decomposition of the integrand function of G1 (τ ), G2 (τ ). Figure 2 shows the alternative Appl. Sci. 2017, 7, 1118 5 of 21 relation of the surface vertical displacement uz (r, 0, t) with the change of τ.

= Figure Relation between surface vertical displacement u(z (,r,0,0, )t) and and τ. . Figure 2. 2. Relation between thethe surface vertical displacement

) on Since normalconcentrated concentratedload load actstheonorigin the origin (Figure and the load is Since a normal QH (t) (acts o (Figure 1), and the1), load is symmetrical symmetrical z-axis, this time is a constant force. For the vibratory roller, force to the z-axis, to Q the at this time is aat constant force. For the vibratory roller, the exciting forcethe Q0exciting is introduced is introduced thewhen centrifugal force when the eccentric oscillator is speed. rotated Itatisa related high speed. by the centrifugalby force the eccentric oscillator is rotated at a high only It to isthe related only to the M static eccentricity and theωangular frequency the vibrator. In with the static eccentricity the angular frequency of the vibrator. In ω theofvibration system e and vibration withforce damping, a periodic forcean must be exerted an external source to maintain damping,system a periodic must be exerted from external sourcefrom to maintain the vibration. Generally, the Generally,isthe excitation is the main force, androller the vibration wheel the the vibration. harmonic excitation theharmonic main force, and the vibration wheel of the works under the of simple roller works under theAssuming simple harmonic Assuming that the vibration system is subjected harmonic excitation. that theexcitation. vibration system is subjected to a simple harmonic load of ( ) = cos uz, of to harmonic of displacement the vertical of theunder soil on semiQ(atsimple ωt, theload vertical the soil ondisplacement the semi-space surface thethe action of ) = Q0 cos space surface under the action of the simple harmonic load needs to be solved. In this study, an the simple harmonic load needs to be solved. In this study, an innovative differential pulse excitation innovative differential excitation method was proposed, thetodifferential pulse excitation method was proposed,pulse and the differential pulse excitation wasand used simulate the harmonic load was used to harmonic load excitation to solve the vertical displacement. The specific excitation to simulate solve the the vertical displacement. The specific method is as follows: method is as follows: (1) Firstly, the periodic harmonic load excitation is discretized into N parts, then the Nth excitation (1) Firstly, load in excitation pulse isthe Qnperiodic (n ∈ [1, harmonic N ]), as shown Figure 4.is discretized into N parts, then the Nth excitation pulse is ( ∈ [1, ]), as shown in Figure 3. (2) Then, assuming Qn = Qn ((n − 1)∇τ ) H (t + (n − 1)∇τ ) − Qn (t + (n − 1)∇τ ) H (t + n∇τ ), ( − 1)∇ ( + ( − 1)∇ ) − ( + ( − 1)∇ ) ( + ∇ ) , ∇τ is (2) Then, assuming = ∇τ is the delay time and Qn ((n − 1)∇τ ) = Q0 cos(ω (n − 1)∇τ ), as shown in Figure 3. ( − 1)∇ = cos( ( − 1)∇ ), as shown in Figure 4. the delay time and (3) Impulse excitation Q1 , Q2 , Q3 , Q4 , · · · , Qk , · · · , Q N are applied to the origin o, respectively, , , , ,k⋯ , , ⋯ , are applied to the origin , respectively, and the (3) Impulse excitation and the vertical displacement u (k ∈ [1, N ]) at the distance r from the origin o is obtained when vertical displacement ( ∈ [1, ]) at the distance from the origin is obtained when the the different pulse loads act on the semi-space surface. When [0, t], (t ∈ [0, 2π]), the true vertical different pulse loads act on the semi-space surface. When [0, ], ( ∈ [0, 2π]), the true vertical displacement uz of the soil under the simple harmonic load Q(t) = Q0 cos ωt at any time in displacement of the soil under the simple harmonic load ( ) = cos at any time in a a cycle can be obtained by integrating the vertical displacement response of the pulse excitation. cycle can be obtained by integrating the vertical displacement response of the pulse excitation. The displacement uz is as follows: Z t The displacement is as follows: uz = uk dt, (3) 0 = , (3) where k ∈ [1, t/∇τ ] and t/∇τ is an integer. where ∈ [1, ⁄∇ ] and ⁄∇ is an integer. Toensure ensurethe theaccuracy accuracyof ofthe thewaveform waveformand anddisplacement displacementas asshown shownin inFigure Figure4,3,let let ∇ 0.001s, To ∇ τ==0.001s, then N = = 22π/ 6283.ByBy utilizing above method solve vertical displacement under ⁄∇∇τ≈ ≈ then 6283. utilizing thethe above method to to solve thethe vertical displacement under a a simple harmonic load, the required vertical displacement can be obtained by combining the research simple harmonic load, the required vertical displacement can be obtained by combining the research resultofofPekeris Pekerisand andrelevant relevant data. Figure 5 shows the change ofvertical the vertical displacement result data. Figure 5 shows the change of the displacement whenwhen = t = 500 ∇ τ, 1000 ∇ τ, 4000 ∇ τ, 6283 ∇ τ, respectively. 500∇ , 1000∇ , 4000∇ , 6283∇ , respectively.

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Figure 3. Periodic simple harmonic load excitation discretization. Figure 3. Figure Schematic diagram of pule load formed by differential concentrated load. harmonic loadexcitation excitation discretization. Figure3.3.Periodic Periodic simple simple harmonic load discretization.

=1 = = 11

1

( ) 11 ( () ) 0 00 ∇ − 1 ( +∇ ) 1 ∇∇ −−1 ( (++∇∇) )

( + ( − 1)∇ ) (( ++(( −−1)∇ 1)∇) ) (k − 1)∇ (k − 1)∇ 0 (k − 1)∇ 00

− − −

( + ∇ ) (( ++ ∇∇) )

= ==

k∇ k∇ k∇

( , 0, ) ( , )0, ) ( , 0,

() , )0, ) ( (, 0,, 0,

Figure 4. Periodic simple harmonic load by excitation discretization. Figure 4. Schematic diagram of pule load formed differential concentrated load. Figure 4. Schematic diagram of pule load formed by differential concentrated load. Figure 4. Schematic diagram of pule load formed by differential concentrated load.

(b) = 1000 (b) = 1000 (b) = 1000

= 500 = 500 = 500 ( , )0, ) ( , 0,( ,)0,

( , 0, ) ( , )0, ) ( , 0,

(a) (a) (a)

(c) (c)

= 4000 = 4000

(d) (d)

= 6283 = 6283

Figure 5. Change curve of vertical displacement at different (c) (d) times. = 4000 = 6283 Figure displacementat atdifferent differenttimes. times. Figure5.5.Change Changecurve curve of of vertical vertical displacement

Figure 5. Change curve of vertical displacement at different times.

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By solving the problem, the real vertical displacement uz of the soil on the surface of the semi-space Appl. Sci. 2017, 7, 1118 7 of 21 at any time in a cycle under the harmonic load Q(t) = Q0 cos ωt can be obtained as follows: By solving the problem, the real vertical displacement of the soil on the surface of the semiQ 0 ) = t, cos space at any time in a cycle under theu harmonic load (cosω can be obtained as follows:(4) z (r, 0, t ) = 0 A0 πGr ( , 0, ) = , (4) where A0 = 0.03605 and ω0 = 2π/T0 , T0 = 0.036 s. ⁄ , = 0.036 where = 0.03605 and vertical = 2 displacement To solve the real-time ofs.multiple cycles, the displacement function of To solve theneeds real-time Equation (4) just to be vertical shifted. displacement of multiple cycles, the displacement function of Equation (4) just needs to be shifted. 2.1.2. Infinite Baffle Piston Radiation Acoustic Field 2.1.2. Infinite Baffle Piston Radiation Acoustic Field Figure 6a shows a circular piston radiator on an infinite baffle. When the piston vibrates at iωt of in the z direction, the radiator radiates the acoustic wave to the semi-infinite the speed u= Figure 6a ushows a circular piston radiator on an infinite baffle. When the piston vibrates at the Ae space baffle. InzFigure 6b, athe surface element withthe an area of dSwave and atodistance of q from speedin front = of theof in the direction, radiator radiates acoustic the semi-infinite the center of the is selected. Since field acoustic wave is studied this surface space in front ofpiston the baffle. In Figure 6b,far a surface element withradiation an area of andhere, a distance of element be considered as aispoint source, and entire pistonwave radiator is made of many point from thecan center of the piston selected. Since farthe field acoustic radiation is up studied here, this sources. Based on materials thesource, literature, fieldpiston radiation sound pressure is surface element canteaching be considered as aand point andthe thefar entire radiator is made up of described as follows: many point sources. Based on teaching materials and the literature, the far field radiation sound aρ cu J (kasinθ ) i(ωt−krP ) pressure is described as follows: p = i 0 A 1 e . (5) 2r P sinθ ( ) ( ) = For an N order first class Bessel function, if n is a positive integer. or zero, Γ(n + m + 1) = (n + m(5) )!. In addition, considering the relation between the zero-order and the first-order Bessel functions, For an N order first class Bessel function, if is a positive integer or zero, assign following formula is obtained: ( +n= + 0, 1) n== ( 1,+the)!. In addition, considering the relation between the zero-order and the firstorder Bessel functions, assign3 = 0, 5 = 1, the 7following formula is obtained: x x x x x2k+1 J1 ( x ) = − 3 + 5 − 7 + · · · + (−1)k 2k+1 +··· . 2 ( )2 =·2! − 2 ·2!3! 2 −·3!4! + ⋯ + (−1) 2 k!(k + 1+)!⋯. + ∙ !

∙ ! !

∙ ! !

!(

)!

Considering of the acoustic far field, relations relations are obtained: Considering the thecharacteristics characteristics of the acoustic far there field,following there following are 2 /l. According to the small quantity property of the Bessel function, when x → 0 , robtained:  a, r  a P P ⁄ ≫ , ≫ . According to the small quantity property of the Bessel function, substituting following is obtained: 1 ( x ) into Equation ( ) (5), intothe Equation (5), formula the following formula is obtained: when → 0, Jsubstituting p((r P ,,t)) = =i

ka2 ρ0 cu A

h

11 11 (kasinθ )2 ) ( − 16 22− 16 ei(ωt(−krP ) ≈)

i

2r2P

(a)

ka2 ρ0 cu A i(ωt− ( kr P ) i e ≈ 4r P4

)

(6) (6)

(b)

Figure 6. 6. (a) piston on on infinite infinite baffle; baffle; (b) (b) radiated radiated acoustic acoustic field field of of circular circularpiston. piston. Figure (a) Circular Circular piston

2.1.3. Analytical Solution In acoustics, the sound pressure and particle velocity often need to be computed. For the ease of calculation, plural forms are often used to express these physical quantities. The speed of the piston

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2.1.3. Analytical Solution In acoustics, the sound pressure and particle velocity often need to be computed. For the ease of calculation, plural forms are often used to express these physical quantities. The speed of the piston in the z direction can be written as u = u A cosωt, and the displacement of the piston in the z direction is as follows: Z u0z =

t

0

udt = u A sinωt.

(7)

When τ = 1.088, Rayleigh will arrive, and τ = c T t0 /r = 1.088, therefore t0 = 1.088r/c T . p Since c T = G/ρ, at time t0 , the boundary condition between the soil and the air medium can be described by Equation (8): (8) u0z t=t0 = uz (r, 0, t0 ). Substituting Equation (4) and Equation (7) into Equation (8), since k = ω/c, where k is the wave number, ω is the angular frequency, and c is wave velocity, Equation (9) is obtained: r    ρ 1 Q0 k = arcsin cos 1.088ω0 r . c πGru A G

(9)

Substituting Equation (9) into Equation (6), the sound pressure expression is obtained: p (r P , t ) = i

r    a2 ρ0 u A Q0 ρ cos 1.088ω0 r ei(ωt−krP ) , arcsin 4r P πGru A G

(10)

where uA = p0 /ρ0 c0, p0 is the standard atmospheric pressure at ambient temperature, c0 is the propagation velocity of the acoustic wave in the air medium at ambient temperature, ρ is the mass density of the soil, and µ is the shear modulus of the soil. After Equation (10) is carried on by FFT, the root mean square (RMS) amplitude can be obtained. In Equation (11), b0 is a constant: r    ρ a2 ρ0 u A Q0 A= cos 1.088ω0 r . b0 arcsin 4r P πGru A G

(11)

Lade and Nelson [46] developed a nonlinear isotropic model for the elastic behavior of granular materials. In their research, the Young’s modulus is expressed as in Equation (12): " E = Mp a

I1 pa

2

J0 + R 22 pa

#λ .

(12)

Based on Lade and Nelson, Liu et al. [47] carried out a constitutive modeling research of dense gravelly soils subjected to cyclic loading. In their paper, modulus G is further expressed as Equation (13): G = G0 p a

K J (2.97 − e)2 3p 2 [( ) + 9 0 22 ] 1+e pa G0 p a

m/2

,

(13)

where G is the shear modulus, G0 and m are material constants, e is the current void ratio, and p a is the atmospheric pressure. Substituting Equation (13) and e = 1 − ρ0 /ρ into (11), Equation (14) is obtained:  ! q a2 ρ0 u A b0 Q0 M0 2ρ2 − ρρ0 ρ A= arcsin cos 1.088ω0 r M0 (2ρ − ρ0 ) , 4r P πru A (1.97ρ + ρ0 )2 1.97ρ + ρ0

(14)


m/2 where M0 = G0 p a [(3p/p a )2 + 9(K0 /G0 ) J2 /p2a ] , ρ is the mass density, and ρ0 is the dry density.

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A diagrammatic sketch of the compacting area in pulse load duration time (∆τ) is shown in Figure 7. The velocity of the roller is v. As mentioned above, the harmonic load is discretized into N parts (Figure 4). The duration of each pulse load is ∆τ. The compaction area during the time interval ∆τ is illustrated as rectangle ABCD in Figure 7. At this point, the area ABCD can be considered to consist of Nc rows and Mc columns of small piston radiators. Then the radiation field generated by the interaction between the vibration wheel and the soil is composed of Nc rows and Mc columns of small piston radiators on the infinite baffle. The radius for each piston is a = 0.01 cm, and since the length of the vibration wheel is L = 2.2 m, the number of pistons in each column is Nc = L/2a = 11, 000, Appl. Sci. 2017, 7, 1118 9 of 21 and the number of pistons in each row is Mc = v∆τ/2a, Mc ∈ Z. Filling and compacting area M columns D A Small piston

⋯

⁄2 ⋮ ⋮

Roller trajectory

⋮ ⋮

⋯ ⋯

A total of NN ⋮ ⋮

Strip central line Compaction strip

⋮ ⋮

⁄2 ⋯

B

C Compacting area in pulse load duration time (∆ )

Figure 7. Diagrammatic sketchofofcompacting compacting area duration time (∆ ).(∆τ). Figure 7. Diagrammatic sketch areain inpulse pulseload load duration time

When there is an interaction between the vibration wheel and the soil, the result of the joint

When there is an interaction between the vibration wheel and the soil, the result of the joint action action of all piston radiation acoustic fields in the far field point is as follows: of all piston radiation acoustic fields in the far field P point is as follows: =2

⁄

A Rr Aall = 2Mc r P N/2 Adr P  2 2 P0 rP /2   (15) (15) p 2ρ u 0 M b 0 0 2 2ρ2− 0 M 0 a − ρρ ρ Q c N/2 0 0 0 A 0 0 arcsin 1.088 0 r − ) . 0 (2 M == 22 ln rP arcsin . 0 (2ρ −0 ρ0 ) πru A(1.97 + )22 cos 1.088ω01.97 1.97ρ+ + ρ0 A

0

0

(1.97ρ+ρ0 )

0

Based on Equation (15), the theoretical relation model of SHA and the dry density of the soil

Based on Equation (15), the theoretical relation model of SHA and the dry density of the soil were were established and it was called the A-model. established and it was called the A-model. 2.1.4. Numerical Solution

2.1.4. Numerical Solution

In this section, a numerical result is presented for A-model, established in this paper. All the

In this section, numerical resultare is coded presented A-model, established in this paper. All the parameters and a theoretical models usingfor MATLAB language. The numerical solution parameters theoretical models codedby using MATLAB The numerical solution related relatedand to gravel materials was are validated comparing withlanguage. results computed from the field test basedmaterials on the new detection technique in this paper and to gravel wascompaction validated by comparing withproposed results computed from thetraditional field test point based on measurements (water-filling method) inproposed Section 4. Table key parameters for the new compaction detection technique in this1 represents paper andthe traditional pointrequired measurements the numerical analysis. Figure 8 shows the relation curve between the dry density of certain gravel (water-filling method) in Section 4. Table 1 represents the key parameters required for the numerical materials and the SCV based on A-model. The result represents an approximately linear relation analysis. Figure 8 shows the relation curve between the dry density of certain gravel materials and between the SCV and the dry density of the gravel materials. the SCV based on A-model. The result represents an approximately linear relation between the SCV and the dry density of theTable gravel materials. 1. Key parameters required for the numerical analysis. Parameter Parameter Value Parameter Table 1.Value Key parameters required for the numerical analysis. /m p /Pa /cm ≤ 10 10 /(kg ∙ m ) 1.2 3.14 /(g ∙ cm ) Parameter Value Parameter Value Parameter /(m ∙ s ) 340 /(g ∙ cm ) 2.0~2.5 /(rad ∙s ) p0 /Pa
r/m 105 ≤22.6 10−6 0.375 /cm /(ga/cm ∙ cm −3)
0 − 3 1.2 π 3.14 ρ0 / kg·m
ρ/ g·cm

340 2.0 ∼ 2.5 ρ0 / g·cm−3 c 0 / m ·s−1 ω0 / rad·s−1
m0 0.375 r P /cm 22.6 ρ/ g·cm−3

Value 0.01 2.2 Value 174.5 0.01 2.2 2.2 174.5 2.2

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3.6 3.6

Gravel material Gravel material

3.4 3.4

SCV SCV

3.2 3.2 3 3 2.8 2.8 2.6 2.6 2.4 1900 2.4 1900

2000 2000

2100 2100

2200 2200 0 /( 0 /(

2300 2300 ∙ 3) ∙ 3)

2400 2400

2500 2500

2600 2600

Figure Relationcurve curvebetween between dry dry density density of based onon A-model. SCV: Figure 8. 8. Relation of gravel gravelmaterials materialsand andSCV SCV based A-model. SCV: Figure 8. Relation curve between dry density of gravel materials and SCV based on A-model. SCV: sound compaction value. sound compaction value. sound compaction value.

2.2. Technical Implementation

2.2.2.2. Technical Implementation Technical Implementation In this study, a roller-integrated acoustic wave detection technique was developed that includes In this study, a roller-integrated techniquewas wasdeveloped developed that includes In this study, a roller-integratedacoustic acousticwave wave detection detection technique that includes two parts, detection and signal analysis. The schematic diagram of this technique is shown in Figure parts, detection and signal analysis.The Theschematic schematicdiagram diagram of of this this technique technique is twotwo parts, detection and signal analysis. is shown shownin inFigure Figure 9. 9. The detection principle is explained above. This technique has the characteristics of non-contact, 9.detection The detection principle is explained above.This Thistechnique technique has the characteristics of of non-contact, Thehigh principle is explained above. has the characteristics non-contact, efficiency, high precision, continuousness, and convenience. It is suitable for rockfill materials. high efficiency, high precision, continuousness,and andconvenience. convenience. It high efficiency, high precision, continuousness, It isissuitable suitablefor forrockfill rockfillmaterials. materials.

Figure 9. Schematic diagram of acoustic wave detection technique. Figure 9. Schematic diagram of acoustic wave detection technique.

Figure 9. Schematic diagram of acoustic wave detection technique.

As shown in Figure 9, the detection device (2) includes an acoustic field microphone (3), a As shown in Figure 9, the detection device (2) includes an acoustic field microphone (3), a microphone mounting device (10), a signal conditioning module (4), a data acquisition module (5), As shownmounting in Figuredevice 9, the detection device (2) includes an aacoustic field microphone microphone (10), a signal conditioning module (4), data acquisition module (5),(3), an analysis processing module (6), a display (7), and a GPS receiver (9). Moreover, the system also a microphone mounting device (10), a signal conditioning module (4), a data acquisition module an analysis processing module (6), a display (7), and a GPS receiver (9). Moreover, the system also(5), includes a vibratory roller (1) and an onboard battery (11). The sound field microphone (3) is mainly an analysis module (6), an a display and (11). a GPS receiver (9). Moreover, also includes aprocessing vibratory roller (1) and onboard(7), battery The sound field microphonethe (3) system is mainly utilized to receive acoustic field time-domain signals. The signal conditioning module (4) is utilized utilized to receive roller acoustic signals. (11). The signal conditioning module (4) (3) is utilized includes a vibratory (1)field and time-domain an onboard battery The sound field microphone is mainly to convert the signal received by the sound field microphone (3) into a standard signal by means of to convert the signal received by the sound field microphone (3) into a standard signal by of utilized to receive The conditioning (4)means is utilized amplification andacoustic filtering.field Thentime-domain the standard signals. signal can be signal collected by the data module acquisition module amplification and filtering. Then standardfield signal can be collected by the data acquisition module to (5), convert signal received by the the microphone (3) into a standard signal by means whichthe simultaneously acquires thesound spatial signal associated with the roller position provided by (5), which simultaneously acquires the spatial signalsignal associated with the rollerby position provided by of the amplification and filtering. Then the standard can be collected the data acquisition GPS receiver (9). Subsequently, two signals are transmitted to the analysis processing module (6) the GPS receiver (9). Subsequently, two signals are transmitted to the analysis processing module (6) module (5),wired which simultaneously spatial signal withtothe roller position through communication. Theacquires analysisthe processing moduleassociated (6) is utilized implement the through wired communication. The analysis processing module (6) is utilized to implement the provided byspectrum the GPS receiver two signals to the analysis filtering, analysis, (9). andSubsequently, logarithmic processing of are thetransmitted acoustic signal, obtain SHAprocessing of the filtering, spectrum analysis, and logarithmic processing of the acoustic signal, obtain SHA of the module (6) acoustic through signal, wired calculate communication. The analysis processing module (6)coefficient is utilizedintoreal implement effective the SCV values multiplied by the calibration time, effective acoustic signal, calculate the SCV values multiplied by the calibration coefficient in real time,

the filtering, spectrum analysis, and logarithmic processing of the acoustic signal, obtain SHA of

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the effective acoustic signal, calculate the SCV values multiplied by the calibration coefficient in Appl. Sci. 2017, 7, 1118 11 of 21 real time, deal with the spatial signals related to the roller position by the differential algorithm, anddeal calculate thespatial current position coordinate of vibration roller (centimeter level). The (7) is with the signals related to the roller position by the 1differential algorithm, anddisplay calculate utilized to display the real-time compaction nephogram with the spatial location characteristic the current position coordinate of vibration roller 1 (centimeter level). The display (7) is utilized toand display other relevant compaction information on the spot, such as the location drivingcharacteristic speed, compaction monitoring display the real-time nephogram with the spatial and display other information, number of compaction and on. Thespeed, GPS receiver (9) ismonitoring utilized to information, acquire spatial relevant information on the spot, times, such as thesodriving compaction signal information relatingtimes, to theand roller The RTK-GPS satellite, and GPS base station number of compaction so position. on. The GPS receiver (9)receiver, is utilized to acquire spatial signal information to theThe roller position. The RTK–GPSdevice receiver, andto GPS station fix fix the position relating of the roller. microphone installation (10)satellite, is utilized fix base the acoustic field the position the roller.isolation The microphone installation device (10) utilized to fix microphone the acoustic field microphone (3).ofVibration of the contact parts between theisacoustic field (3) and Vibration of the contactthe parts between the acoustic field (3) and themicrophone installation(3). device (10), isolation as well as between installation device (10) andmicrophone the vibratory roller the installation device (10), as well as between the installation device (10) and the vibratory roller (1), (1), is implemented by soft rubber. The onboard battery (11) provides power support for the entire is implemented by soft rubber. The onboard battery (11) provides power support for the entire continuous compaction control acoustic wave detection system. continuous compaction control acoustic wave detection system.

2.3. Sound Compaction Value 2.3. Sound Compaction Value

During rolling construction, the compacted layer is synthetically affected by the static pressure During rolling construction, the compacted layer is synthetically affected by the static pressure and vibration force. The comprehensive effect can change the material’s status from static to vibrating, and vibration force. The comprehensive effect can change the material’s status from static to vibrating, then reduce the friction force and cohesion between soil (or rock) particles. Thus, small soil (or rock) then reduce the friction force and cohesion between soil (or rock) particles. Thus, small soil (or rock) particles fill the voids between larger particles and the material gradually becomes dense. When rolling particles fill the voids between larger particles and the material gradually becomes dense. When construction begins, filling materials are relatively loose (Figure 10a), the sound pressure curve is rolling construction begins, filling materials are relatively loose (Figure 10a), the sound pressure relatively (Figure 10d), the corresponding sound spectrum predominant at the fundamental curve issmooth relatively smooth (Figure 10d), the corresponding soundisspectrum is predominant at the frequency ( f ), and the amplitude of the SCV is relatively low (Figure 10g). With an increase 0 fundamental frequency ( ), and the amplitude of the SCV is relatively low (Figure 10g). With an in theincrease numberin of the compactions, compactedthe material becomes more dense (Figure 10b), (Figure and the10b), higher number of the compactions, compacted material becomes more dense harmonic gradually increase (Figure 10e). (Figure Meanwhile, the SCVs the change and the components higher harmonic components gradually increase 10e). Meanwhile, SCVs gradually change (Figure 10h). (Figure As the 10h). number of compaction times increases to a certain content of higher gradually As the number of compaction times increases to adegree, certain the degree, the content harmonic components tends to be stable (Figure 10f), and the compacted material becomes denser and of higher harmonic components tends to be stable (Figure 10f), and the compacted material becomes denser tends to be stable 10c). The SCVs further to(Figure be stable10i). (Figure tends to beand stable (Figure 10c). (Figure The SCVs further change andchange tend toand be tend stable This10i). paper This paper defines a real-time SCV as the compaction index for characterizing the compaction defines a real-time SCV as the compaction index for characterizing the compaction status ofstatus rockfill of rockfill materials as follows: materials as follows: SCV ==k ××SHA SCV SHA× × 100%, 100%, (16)(16) where k is the coefficient of the material. where is calibration the calibration coefficient of the material.

0

2

0

3

0

4

0

5

0

0

2

0

3

0

4

0

5

0

0

2

0

3

0

4

0

5

0

Figure Illustrationofofchanges changesin insound sound pressure pressure and stiffness. Figure 10.10. Illustration and SCV SCVwith withincreasing increasingground ground stiffness.

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Percent Finer by Weight(%)

3. Case Study 3. Case Study 3.1. Testing Site and Materials 3.1. Testing Site and Materials A reservoir project is located in Henan Province, China. The main structures include the main project in Henan China. The main structures include theismain dam, dam,Aanreservoir auxiliary dam,isa located spillway, a waterProvince, tunnel, and a power station. The main dam a rockfill an auxiliary dam, a spillway, a water tunnel, and a power station. The main dam is a rockfill dam dam with a maximum height of 90.3 m. This experimental research focused on the NGM atwith the a maximum height ofas 90.3 m. This experimental the NGM the upstream cofferdam upstream cofferdam a part of the main dam.research During focused the earlyonstage of theatreservoir project, IWHR as a part of the main dam. During the stage of the reservoir project, (China Institute of (China Institute of Water Resources andearly Hydropower Research) carried outIWHR a gravel material rolling Water Resources and Hydropower Research) carried out a gravel material rolling test. The grading test. The grading curve of the gravel material taken from VI zone material field is shown in Figure 11. curve of the gravel material taken fromofVItest zone material field is shown Figure 11. In grading the five In the five sets of tests, only one group materials was graded in theinrepresentative sets of tests, only one group of test materials was graded in the representative grading envelope, envelope, and the others were graded beyond the original grading. Taking into account the great and theofothers were graded original grading. Taking account the greatsize change of change the gravel materialbeyond in eachthe material field, the NGM hadinto a maximum particle of 200 the gravel in each material field,The thetest NGM had acarried maximum sizeindicated of 200 mm based mm based material on a conservative estimate. results out particle by IWHR that the on a conservative estimate. The test results carried out by IWHR indicated that the proportion of proportion of particles less than 5 mm was 8–26%, and the proportion of particles more than 200 mm particles less than 5 mm was 8–26%, and the proportion of particles more than 200 mm was 1.3–7.1%. was 1.3–7.1%. The maximum size of the natural gravel material was up to 400 mm, and the content The maximum gravel material to 400 mm, and the content particles of particles less size thanof5 the mmnatural was controlled withinwas 15%.up The designed standard of theof dry densityless of than 5 mm was controlled within 15%. The designed standard of the dry density of the NGM was the NGM was greater than 2.144 g/cm3, and compactness needed to be greater than 75% according to 3 , and compactness needed to be greater than 75% according to the design greater than 2.144 g/cm the design criteria. Due to a wide range of particle size distribution for NGM and above analysis, we criteria. Due to aiswide range offor particle size distribution for and above analysis, we know that know that CMV not suitable this material. Therefore, it NGM is necessary to propose a new technique CMV is not suitable for this material. Therefore, it is necessary to propose a new technique to detect to detect the compactness of NGM quickly and accurately. the compactness of NGM quickly and accurately. 100 90 80 70 60 50 40 30 20 10 0

NO.1 Sample W=4253kg NO.2 Sample W=4681Kg NO.3 Sample W=5204Kg NO.4 Sample W=3650Kg NO.5 Sample W=3951Kg Upper Envelope Curve Lower Envelope Curve

1000

100

10

1

0.1

0.01

Gravel Material Grain Size(mm) Figure 11. Grading curve of gravel material taken from in situ VI zone material field.

Figure 11. Grading curve of gravel material taken from in situ VI zone material field.

3.2. Testing Program

3.2. Testing Program To analyze the effectiveness of SCV for assessing the compaction quality of rockfill materials, a two-part field the experiment was performed. The first part of the experiment thematerials, correlation To analyze effectiveness of SCV for assessing the compaction qualitystudied of rockfill a between the compaction parameters and SCV. Four testing strips were filled with NGM with consistent two-part field experiment was performed. The first part of the experiment studied the correlation moisture the content and gradation. Eachand strip hadFour a length of 30 m and a width 3 m.NGM Figure 12 between compaction parameters SCV. testing strips were filled of with with shows photos of the field and rolling test inEach the rock-fill located 1 of and Elevation consistent moisture content gradation. strip hadzone a length of 30in m Elevation and a width 3 m. Figure 122 (upstream cofferdam), and the test scheme is shown in Table 2. NGM represents natural gravel shows photos of the field rolling test in the rock-fill zone located in Elevation 1 and Elevation 2 materials, and HFHA represents high-frequency/high-amplitude. The second part of the experiment (upstream cofferdam), and the test scheme is shown in Table 2. NGM represents natural gravel was traditional point measurements (water-filling method) aimed atThe analyzing between materials, and HFHA represents high-frequency/high-amplitude. second the partcorrelation of the experiment SCV and the number of compaction times as well as the compactness of the NGM. was traditional point measurements (water-filling method) aimed at analyzing the correlation between SCV and the number of compaction times as well as the compactness of the NGM.

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Figure Photos of Figure 12. 12. Photos of field field rolling rolling test test in in the the rockfill rockfill zone. zone. Table 2. Table 2. Test Test scheme scheme for for field field rolling rolling experiment. experiment.

Material Strip Material Strip NGM NGM

1~4 1~4

Passes Passes (Static) (Static) 22

Passes Vibration Frequency Velocity Velocity Passes Vibration Frequency (Vibratory) ( ) ( / ) (Vibratory) (Hz) (km/h) 12 12

31 31

3 3

Lift Lift Thickness Thickness ((m)) About 0.8 About 0.8

Vibration Vibration Status Status HFHA HFHA

To evaluate this technique, the field study was conducted in 30-m test strips (Figure 12) using To evaluate this technique, the field study was conducted in 30-m test strips (Figure 12) using NGM. A set of field data was obtained, including compaction parameters, SCVs and results of NGM. A set of field data was obtained, including compaction parameters, SCVs and results of traditional point measurements that were used for correlation analysis and verifying the effectiveness traditional point measurements that were used for correlation analysis and verifying the effectiveness of this technique. The test strips were compacted using a prototype SSR260C-6 vibratory smooth of this technique. The test strips were compacted using a prototype SSR260C-6 vibratory smooth drum roller. The depth of the filling layer was approximately (and not exceeding) 0.8 m. Test sites of drum roller. The depth of the filling layer was approximately (and not exceeding) 0.8 m. Test sites two different elevations were used for this field test. Each strip was divided into a start region, an of two different elevations were used for this field test. Each strip was divided into a start region, effective rolling region, and a stop region (Figure 12, Strip 4). The length of the start region and the an effective rolling region, and a stop region (Figure 12, Strip 4). The length of the start region stop region was 3 m, and the length of the effective rolling region was 24 m. Considering the diameter and the stop region was 3 m, and the length of the effective rolling region was 24 m. Considering of the test pit in the water-filling method and the accuracy of this technique, the effective rolling the diameter of the test pit in the water-filling method and the accuracy of this technique, the effective region was divided into six blocks (Figure 12). Static compaction was first performed in the four strips rolling region was divided into six blocks (Figure 12). Static compaction was first performed in and then vibration compaction was performed (Table 2). Static compaction and vibration compaction the four strips and then vibration compaction was performed (Table 2). Static compaction and was performed for two times and 12 times, respectively. vibration compaction was performed for two times and 12 times, respectively. 4. Results Results and and Discussions Discussions 4. 4.1. Spectrum Analysis of Detection Results

Field tests testswere wereperformed performedutilizing utilizing a detection device developed in study. this study. Data Field a detection device thatthat waswas developed in this Data from fromtest four test were stripscollected were collected and analyzed. Duelarge to the largeofamount of length data and length four strips and analyzed. Due to the amount data and limitation limitation of this the dataprocess analysisisprocess is illustrated the original data from of this paper, thepaper, data analysis illustrated with the with original acoustic acoustic data from Strip 1. Strip 1.13 Figure 13 represents the original data collected by the acoustic field microphone from Figure represents the original acousticacoustic data collected by the acoustic field microphone from Strip 1 Strip 1 when the number of vibration compaction times is from 1 to 2. It can be seen from Figure 13 when the number of vibration compaction times is from 1 to 2. It can be seen from Figure 13 that thatamplitude the amplitude the sound pressure vibratory compaction, and the magnitude was the of theof sound pressure during during vibratory compaction, and the magnitude was between between −200200 pa and 200 pa. The acoustic signal situation when thestarted roller and started and stopped the − 200 Pa and Pa. The acoustic signal situation when the roller stopped the rolling rolling operation is shown in Figure 13a. Results shown in Figure 13 and from other test strips showed operation is shown in Figure 13a. Results shown in Figure 13 and from other test strips showed that that there in original the original acoustic signal there no obvious change there was was zero zero driftdrift in the acoustic signal andand there waswas no obvious lawlaw for for thethe change of of the time domain signal. the time domain signal. In order order to to perform perform the the spectrum spectrum analysis analysis and and obtain obtain the the SCV, SCV, the the original original acoustic acoustic signal signal for for In each pass pass of of compaction compaction was was processed processed in in the the following following steps: steps: firstly, the signals signals of of the the start start and and stop stop each firstly, the rolling regions were removed, and zero drift was eliminated; then the remaining acoustic signals rolling regions were removed, and zero drift was eliminated; then the remaining acoustic signals were were divided intoblocks, six blocks, block about length (Figure12, 12,Strip Strip4); 4);subsequently, subsequently, divided into six and and eacheach block waswas about 4 m4 m in in length (Figure the effective effectiveacoustic acoustic signals of block each was block was transformed by FFT, respectively, and the the signals of each transformed by FFT, respectively, and the corresponding corresponding frequency spectrum was obtained; next, the magnitude of the spectrum data was frequency spectrum was obtained; next, the magnitude of the spectrum data was converted by log 10 , converted by , and the SHA of each acoustic signal block was obtained, respectively; finally, the SCV was determined using Equation (16). To illustrate the problem, the frequency spectrum of

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Appl. Sci. 2017, 7,each 1118 14 of 21 andAppl. theSci. SHA 2017,of 7, 1118 acoustic signal block was obtained, respectively; finally, the SCV was determined 14 of 21 using Equation (16). To illustrate the problem, the frequency spectrum of signal collected from Block 1 signal collected from Block 1 in Strip 1 was analyzed (Figure 14). In Figure 14, (1)–(8) represent the in Strip was analyzed (Figure In1Figure 14, (1)–(8) represent number of compaction times signal1collected from Block 1 in14). Strip was analyzed (Figure 14). Inthe Figure 14, (1)–(8) represent the number of compaction times from 1 to 8 and the first three peaks correspond to the fundamental number compaction timespeaks from correspond 1 to 8 and the firstfundamental three peaks correspond to the (fundamental from 1 to 8 of and the first three to the wave amplitude f 0 ), the second wave amplitude ( ), the second harmonic amplitude (2 ) and the third harmonic amplitude (3 ). wave amplitude ( (2 ), fthe second harmonic amplitude (2 ) and third harmonic of amplitude (3 ). harmonic amplitude the third harmonic amplitude f 0the ). The magnitude 0 ) and The magnitude of the fundamental wave amplitude ( (3 ) was between 2 × 10 the andfundamental 4 × 10 . 4 4 The magnitude of the fundamental wave amplitude ( ) was between 2 × 10 and 4 × 10other . wave amplitude ) was between 2 ×other 10 and 4 ×showed 10 . Results shown in Figure 14SHA and from Results shown(A inf 0Figure 14 and from strips that the magnitude of the basically Results shown in Figure 14 and from stripsbasically showed that the magnitude of the SHA basically strips showed the magnitude of other the SHA increased as that the number of compaction times increased. increased as the number of compaction increased as the number of compaction times increased. times increased.

5 5

10 10

15 15

30 30

35 35

40 40

300 300 200 200 100 100 0 0 -100 -100 -200 -200 -300 -300 0 0

20 25 Time/s 20 25 Time/s

5 5

10 10

15 15

20 25 Time/s 20 25 Time/s

30 30

35 35

40 40

Sound pressure/pa Sound pressure/pa

Sound pressure/pa Sound pressure/pa

300 300 200 200 100 100 0 0 -100 -100 -200 -200 -300 -300 0 0

Figure Original acoustic signaldata datacollected collected from from Strip 11 by 3. 3. Figure 13. 13. Original acoustic signal by acoustic acousticfield fieldmicrophone microphone Figure 13. Original acoustic signal data collected from Strip 1 by acoustic field microphone 3.

2000 2000

Amplitude/Pa Amplitude/Pa

0 00 0 6000 6000

0.2 0.2

0.4 ( 0.6) 0.4 ( 0.6)

0.8 0.8

0 00 6000 0 6000

0.4 ( 0.6) 0.4 ( 0.6)

0.8 0.8

1 1

0 00 6000 0 6000

Amplitude/Pa Amplitude/Pa

Amplitude/Pa Amplitude/Pa

0.2 0.2

0.2 0.2

0.4 0.4

0.6 0.6

0.8 0.8

1 1

0.2 0.2

0.4 0.4

0.6 0.6

0.8 0.8

1 1

0.2 0.2

0.4 0.4

0.6 0.6

0.8 0.8

1 1

0.4 0.6 0.8 Frequency/kHz 0.4 0.6 0.8 Frequency/kHz

1 1

4000 4000 2000 2000

2000 2000 0.2 0.2

0.4 0.4

0.6 0.6

0.8 0.8

1 1

0 00 6000 0 6000

Amplitude/Pa Amplitude/Pa

Amplitude/Pa Amplitude/Pa

1 1

2000 2000

4000 4000

4000 4000

4000 4000

2000 2000 0 00 0

)

4000 4000

2000 2000

0 00 6000 0 6000

)

2000 2000

4000 4000

0 00 6000 0 6000

(

4000 4000

0 0

20 2 30 0 30

Amplitude/Pa Amplitude/Pa

4000 4000

(

6000 6000

∈ [2 × 104 , 4 × 104 ] 0 ∈ [2 × 104 , 4 × 104 ] 0

Amplitude/Pa Amplitude/Pa

Amplitude/Pa Amplitude/Pa

6000 6000

2000 2000

0.2 0.2

0.4 0.6 0.8 Frequency/kHz 0.4 0.6 0.8 Frequency/kHz

1 1

0 00 0

0.2 0.2

Figure 14. Spectrum analysis of domain signal collected from Block 1 in Strip 1. Figure 14.14.Spectrum signalcollected collectedfrom fromBlock Block 1 in Strip Figure Spectrumanalysis analysis of of domain domain signal 1 in Strip 1. 1.

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4.2. Correlations between Compaction Parameters and SCV 4.2. Correlations between Compaction Parameters and SCV Based on the analysis described above, SCV was determined. As for the relation between the Based on the analysis described above, SCV was determined. As for the relation between the number of compaction times and SCV, a series of field tests were conducted to the NGM at the main number of compaction times and SCV, a series of field tests were conducted to the NGM at the main dam. Figure 15 shows the correlation between SCV and the number of compaction times in strip 1. dam. Figure 15 shows the correlation between SCV and the number of compaction times in strip 1. The linear correlation between SCV and the number of compaction times ranging from 1 to 8 was The linear correlation between SCV and the number of compaction times ranging from 1 to 8 was analyzed. For each test strip, SCV at each of the six blocks within the strip was calculated during each analyzed. For each test strip, SCV at each of the six blocks within the strip was calculated during each the compaction. In this figure, SCV for NGM increased with the increase of the number of compaction the compaction. In this figure, SCV for NGM increased with the increase of the number of compaction times. SCV computed for each block within each strip had a strong linear relation with the number times. SCV computed for each block within each strip had a strong linear relation with the number of of compaction times, and the determination coefficient ( ) ranged from 0.7803 to 0.9696, respectively. compaction times, and the determination coefficient (R2 ) ranged from 0.7803 to 0.9696, respectively. The specific determined coefficient ( 2 ) was shown in Table 3. The specific determined coefficient (R ) was shown in Table 3.

Figure Figure 15. 15. Correlation Correlation between between the the SCV SCV and and the the number number of of compaction compaction times times in inStrip Strip1. 1. 2 Table Table3.3.Specific Specificdetermined determinedcoefficient coefficient(R ( ))between between the the SCV SCV and and the thenumber number of ofcompaction compaction times times for NGM. for NGM.

Strip Strip 1 1 Block Block 1 0.8972 1 0.8972 2 0.8461 2 0.8461 3 0.8342 3 0.8342 4 0.7803 4 0.7803 5 0.9001 5 0.9001 6 0.8010 6 0.8010

22 0.8085 0.8085 0.8316 0.8316 0.8775 0.8775 0.8628 0.8628 0.7961 0.7961 0.8619 0.8619

3

3

0.8147 0.8147 0.8237 0.8237 0.9696 0.9696 0.9232 0.9232 0.8679 0.8679 0.7955 0.7955

4

4

0.9096 0.9204 0.8416 0.8052 0.8714 0.8968

0.9096 0.9204 0.8416 0.8052 0.8714 0.8968

4.3. Correlations between SCV and Compaction Quality of Rockfill Materials 4.3. Correlations between SCV and Compaction Quality of Rockfill Materials In the upstream cofferdam construction area, field tests at four strips were conducted to obtain In the upstream cofferdam construction area, field tests at four strips were conducted to obtain the dry density, compactness, and other property parameters of the rockfill materials (P5 content, the dry density, compactness, and other property parameters of the rockfill materials ( content, minimum dry density, and maximum dry density). In total, 16 groups of data were collected for minimum dry density, and maximum dry density). In total, 16 groups of data were collected for correlation analysis. Figure 16 shows the correlation between the SCV and the dry density as well correlation analysis. Figure 16 shows the correlation between the SCV and the dry density as well as as between the SCV and the compactness when the number of compaction times is 6, 8, 10, and 12, between the SCV and the compactness when the number of compaction times is 6, 8, 10, and 12, respectively, in strip 1. The correlation between the SCV and the dry density as well as the correlation respectively, in strip 1. The correlation between the SCV and the dry density as well as the correlation between the SCV and the compactness had similar trends, i.e., while the SCV increased, the dry density between the SCV and the compactness had similar trends, i.e., while the SCV increased, the dry and the compactness also increased and vice versa. The relation between the SCV and the compactness density and the compactness also increased and vice versa. The relation between the SCV and the is shown in Figure 17. It evidently exhibits a strong linear relation with the determination coefficient compactness is shown in Figure 17. It evidently exhibits a strong linear relation with the R2 ranging from 0.7371 to 0.8064. Since the SCV strongly correlates to the compactness, the SCV is determination coefficient ranging from 0.7371 to 0.8064. Since the SCV strongly correlates to the an effective index that reflects the compaction status of rockfill materials, while the compactness is compactness, the SCV is an effective index that reflects the compaction status of rockfill materials, a key index of the compaction quality of the dam foundation and dam body. while the compactness is a key index of the compaction quality of the dam foundation and dam body.

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Compactness Compactness (%) (%)

Compactness Compactness (%) (%)

Compactness Compactness (%) (%)

Compactness Compactness (%) (%)

Figure 16. SCV, dry density, density, SCV, SCV,and andcompactness compactnessat ateach eachblock blockalong alongStrip Strip1.1. 1. Figure SCV, and compactness at each block along Strip Figure 16. 16. SCV, SCV, dry

Figure 17. 17. Linear Linear correlations correlations between between SCV SCV and and compactness compactness computed computed from fromall alltest teststrips. strips. Figure 17. between SCV and compactness computed from all test strips. Figure Linear correlations

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4.4. Relations between the the Theoretical Theoretical Model Model and and In In Situ Situ Measurements Measurements 4.4. Relations between Figures 16 16 and and 17 17 reflect reflect the the compaction compaction quality quality by by analyzing analyzing the the correlations correlations between between the the SCVs SCVs Figures and the measured values from field tests. To some extent these analyses could reflect the effectiveness and the measured values from field tests. To some extent these analyses could reflect the effectiveness of the the new newdetection detectiontechnique techniqueproposed proposedinin this paper. order to further verify effectiveness of of this paper. In In order to further verify the the effectiveness of this this technique, the relations between the actual from situ measurements and calculated technique, the relations between the actual valuesvalues from in situ in measurements and calculated values values from A-model. The measured values from the field tests were calculated on average the from A-model. The measured values from the field tests were calculated on average when thewhen number number of compaction was 6,12, 8, 10, and 12, respectively, each 18 strip. Figure 18 shows the of compaction times wastimes 6, 8, 10, and respectively, in each strip. in Figure shows the comparison of comparison of the dry density between the actual values and the calculated values based A-model. the dry density between the actual values and the calculated values based on A-model. on The relative The relative errors thedry measured and thevalues calculated values based on A-model errors between the between measured density dry and density the calculated based on A-model are shown are shown in Table 4. The average relative errors of A-model are less than 5%, which means that Ain Table 4. The average relative errors of A-model are less than 5%, which means that A-model has model has high accuracy. high accuracy.

SCV

30 25 20

3.0

15

2.8

Strip 1

2.6

3.6

35

10

3.4 3.2

2000

2200

2400

2000

35 30 20

3.0

15

2.8

Strip 3

2.6

10 5

2.4

(kg/m3)

2400

3.6

0 2600

3.4 3.2

SCV

SCV

40

25

2200

0 2600

2400

(kg/m3)

Actual dry density Calculated dry density of A-Model Relative errors

2000

2200

Actual dry density Calculated dry density of A-Model Relative errors

40 35 30 25 20

3.0

15

2.8

Strip 4

2.6

10

Relative error (%)

3.2

10 5

2.4

Relative error (%)

3.4

30

15

Strip 2

(kg/m3) 3.6

35

20

3.0

2.6

0 2600

40

25

2.8

5

2.4

Actual dry density Calculated dry density of A-Model Relative errors

Relative error (%)

3.2

40

Relative error (%)

3.4

Actual dry density Calculated dry density of A-Model Relative errors

SCV

3.6

5

2.4 2000

2200

2400

0 2600

(kg/m3)

Figure Comparison between between actual actual dry dry density density values values and and calculated calculated values values computed computed by Figure 18. 18. Comparison by A-model. A-model. Table 4. Relative errors errors between Table 4. Relative between measured measured and and calculated calculated dry dry density. density.

Strip Strip 1 1 22 33 4

Maximum Relative Relative Error Relative Maximum RelativeError Error(%) (%) Minimum Minimum Relative Error(%) (%) Average Average RelativeError Error(%) (%) 4.31 0.04 1.63 4.31 0.04 1.63 5.80 2.91 4.74 5.80 2.91 4.74 3.89 0.18 2.39 3.89 0.18 2.39 5.66 2.79 4.58 5.66 2.79 4.58

White and Thompson [15] conducted a field study with 30-m test strips using five granular White and Thompson [15] conducted a field study with 30-m test strips using five granular materials to investigate the correlation between CMV and the compaction quality of granular materials to investigate the correlation between CMV and the compaction quality of granular materials materials in transportation projects. The results of White and Thompson showed that CMV was not in transportation projects. The results of White and Thompson showed that CMV was not suitable suitable for rockfill materials with large particle sizes (>200 mm). Moreover, based on the foregoing for rockfill materials with large particle sizes (>200 mm). Moreover, based on the foregoing analysis, analysis, Liu’s method would not be suitable for NGM (0.1 mm~400 mm). Due to the larger particle Liu’s method would not be suitable for NGM (0.1 mm~400 mm). Due to the larger particle size size distribution of NGM than soil, which is suitable for road construction and earth-rock materials distribution of NGM than soil, which is suitable for road construction and earth-rock materials used used for dam construction, as well as results from White and Thompson’s study, previously for dam construction, as well as results from White and Thompson’s study, previously developed developed detection techniques and methods could not meet the needs of rockfill materials from the detection techniques and methods could not meet the needs of rockfill materials from the reservoir reservoir project in Luoyang, China. As a result, a new compaction detection technique is proposed in this paper. The new compaction detection technique can solve the existing problem and drawbacks

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project in Luoyang, China. As a result, a new compaction detection technique is proposed in this paper. The new compaction detection technique can solve the existing problem and drawbacks in the CMV in the CMV method. The SCV, which is used to detect the compactness of rockfill materials, can method. The SCV, which is used to detect the compactness of rockfill materials, can automatically be automatically be acquired by CAWDS developed in this study, and can directly characterize the acquired by CAWDS developed in this study, and can directly characterize the compaction status of compaction status of rockfill materials (Figure 19). Figure 19 shows the variation of the SCV as the rockfill materials (Figure 19). Figure 19 shows the variation of the SCV as the number of compaction number of compaction times in Strip 1. The overall compaction performance covering 100% of the times in Strip 1. The overall compaction performance covering 100% of the work area can be clearly work area can be clearly determined by the nephogram. determined by the nephogram.

SCV. Figure 19. Compaction nephogram of Strip 1 using SCV.

5. Conclusions Conclusions 5. In this this study, study, aa new new roller-integrated roller-integrated acoustic acoustic wave wave detection detection technique technique was was proposed; proposed; the the SCV SCV In was utilized forfor thethe evaluation of the quality, and an infinite baffle was utilized as asaacompaction compactionindex index evaluation of compaction the compaction quality, and an infinite piston radiation acoustic field model (i.e., A-model) was established to accurately estimate the dry baffle piston radiation acoustic field model (i.e., A-model) was established to accurately estimate density of the NGM. The new was adopted to detect the compactness and and evaluate the the dry density of the NGM. Thetechnique new technique was adopted to detect the compactness evaluate compaction quality in the entire construction area of the upstream cofferdam of aofreservoir project in the compaction quality in the entire construction area of the upstream cofferdam a reservoir project Luoyang, China. The new technique was beneficial to improve the compaction quality and avoid in Luoyang, China. The new technique was beneficial to improve the compaction quality and avoid quality defects. defects. quality The following conclusions conclusions were were drawn. drawn. The following (1) The SCV value increased with the increase of the number of compaction times. Furthermore, the (1) The SCV value increased with the increase of the number of compaction times. Furthermore, SCV increased with the increase of the compactness or dry density and vice versa. Moreover, the SCV increased with the increase of the compactness or dry density and vice versa. the SCV had a strong linear correlation with the number of compaction times ( ranged from Moreover, the SCV had a strong linear correlation with the number of compaction times 0.7803 to 0.9696) as well as the compactness ( ranged from 0.7371 to 0.8064). The comparison (R2 ranged from 0.7803 to 0.9696) as well as the compactness (R2 ranged from 0.7371 to 0.8064). analysis of the actual and calculated dry density based on A-model showed that the relative The comparison analysis of the actual and calculated dry density based on A-model showed errors were between 0.04% and 5.80%, and the average relative errors were less than 5%. that the relative errors were between 0.04% and 5.80%, and the average relative errors were less (2) A-model, namely, a relational model between the SCV and the dry density of the NGM, was than 5%. established. During the modeling process, an innovative differential pulse excitation method (2) A-model, namely, a relational model between the SCV and the dry density of the NGM, was proposed and used to solve the numerical solution of the vertical displacement of the soil was established. During the modeling process, an innovative differential pulse excitation method surface under harmonic loads. The A-model has been experimentally verified to have high was proposed and used to solve the numerical solution of the vertical displacement of the soil accuracy and can meet the requirements of practical projects. surface under harmonic loads. The A-model has been experimentally verified to have high (3) Statistical averaging of in situ measurements in each test strip of the field tests mitigated accuracy and can meet the requirements of practical projects. measurement variations and revealed the high accuracy of the calculated values based on the A(3) model. Statistical of in situ measurements each test specifications strip of the field tests mitigated Thisaveraging data processing method conforms tointhe design of rockfill dams and measurement andonrevealed the high accuracy of the calculated values based on the calculation variations results based the A-model are reliable. (4) Compared with existing contact techniques and methods and CMV-based RICM techniques, the new technique proposed in this paper demonstrated several advantages, such as higher accuracy, smaller discreetness, convenience, and suitability for detecting the compactness of rockfill materials with particle sizes larger than 200 mm. In addition, based on the CAWDS

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the A-model. This data processing method conforms to the design specifications of rockfill dams and the calculation results based on the A-model are reliable. Compared with existing contact techniques and methods and CMV-based RICM techniques, the new technique proposed in this paper demonstrated several advantages, such as higher accuracy, smaller discreetness, convenience, and suitability for detecting the compactness of rockfill materials with particle sizes larger than 200 mm. In addition, based on the CAWDS developed in this study and the RTK-GPS technique, the SCV could automatically be acquired and used to characterize the compaction status of the NGM as a nephogram. Based on the nephogram, the compaction performance in the entire work areas could be clearly determined and support could be provided for quality control in a timely manner. The above results showed that the SCV could serve as a real-time monitoring index characterizing the compaction quality of rockfill dam materials.

Acknowledgments: This work was supported by the National Basic Research Program of China (973 Program, Grant No. 2013CB035902) and the National Natural Science Foundation of China (No. 51339003). The costs to publish in open access have been covered by the funding. Author Contributions: Qinglong Zhang, Qingbin Li, and Tianyun Liu proposed a roller-integrated acoustic wave detection technique for rockfill materials. Qinglong Zhang, Qingbin Li, and Tianyun Liu conceived and designed the experiments. Qinglong Zhang performed the experiments, analyzed the data, and wrote the initial draft of the manuscript. Qingbin Li and Tianyun Liu reviewed and contributed to the final manuscript. Conflicts of Interest: The authors declare no conflict of interest.

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