Case Study: Validation of the Spectral-Analysis-of-Surface-Waves Method for Concrete Pavement Condition Evaluation

Abstract

Before conducting pavement rehabilitation, the concrete pavement performance evaluation is more than necessary to assess the strength and analyze the internal condition. To evaluate the modulus performance of concrete pavement and provide theoretical support for subsequent maintenance and rehabilitation, the SASW (Spectral-Analysis-of-Surface-Waves) method, a non-destructive testing method based on surface waves, was used to determine the modulus of three in-service concrete pavements. At the same time, FWD (Falling Weight Deflectometer) testing and on-site coring were carried out at the measuring points. Through the analysis of modulus results measured in the field, it was found that the SASW method can accurately obtain the elastic modulus of the concrete layer and base layer. Compared with the concrete modulus measured by FWD, the modulus measured by the SASW method was closer to the uniaxial compressive modulus. Moreover, since the SASW method has the ability to provide gradient modulus varying with depth and determine the pavement thicknesses, it is reasonable to recognize the location of the inherent distress based on the region where the modulus suddenly decreases within one layer. The comprehensive evaluation of concrete pavement condition, including the modulus value and internal distress recognition, has the capability to assist in determining the design of overlay asphalt thickness and material.

1. Introduction

The structural behavior of in-service concrete pavements can be considerably affected by the combined influence of traffic loading, climate, and environmental conditions [1]. The dominant distress in the concrete pavement could be considered slab cracking, faulting, spalling, poor ride, delamination, etc. In order to minimize and even eliminate the effects of these distresses, several concrete pavement rehabilitation techniques may be used to prolong and enhance the concrete pavement life, which can be divided into (1) Concrete Pavement Restoration (CPR) techniques; (2) asphalt overlay over existing or fractured concrete pavement; (3) cracking and seating techniques before constructing the asphalt overlay; and (4) bonded/unbonded concrete overlays [2,3]. Meanwhile, the CPR technique also involves full-depth/partial-depth patching, joint and crack resealing, slab stabilization, diamond grinding, load transfer restoration, and cross-stitching longitudinal cracks [4]. Among these rehabilitation techniques, the asphalt overlay over existing concrete pavement is the most common concrete pavement rehabilitation strategy preferred by many agencies, which enhances the structural capacity to extend the service life, lessens the deterioration of pavement, and also minimizes traffic disruptions, especially in urban areas [5]. However, there still exists distress, such as transverse cracking, which could be frequently observed in the asphalt overlay. These distresses are directly affected by three key factors when designing asphalt surfaces: surface preparation, overlay thickness, and material [6]. Therefore, it is significant to carefully design and determine the most targeted pavement rehabilitation process.

Such a decision depends on the condition of the concrete pavement and its evaluation. From an assessment of the concrete pavement’s condition, it is possible to identify the critical area that has a considerable effect on the structure’s performance [7]. Once the evaluation of concrete pavement condition is obtained, which mainly involves strength assessment and internal condition analysis, the rehabilitation process of asphalt overlay could be reasonably determined. During pavement condition evaluation, both direct and indirect measurement methods are frequently employed to characterize the performance of concrete pavement.

Traditionally, the direct measurement method involves extracting core samples from the field, followed by laboratory strength and modulus tests to obtain the necessary characterizations. While this method is straightforward and easy to implement, it has notable drawbacks, including compromising the integrity of the pavement. In contrast, non-destructive testing (NDT) technologies offer the ability to characterize material performances without causing damage to the pavement, thereby preserving the integrity of the pavement system. Due to their increased efficiency, cost-effectiveness, and environmental sustainability, NDT methods are gaining popularity.

Currently, the Falling Weight Deflectometer (FWD), as a commonly used NDT technique, is regarded as a standard method for measuring the elastic modulus of the pavement, base, and subbase layers [8]. However, the back-calculation process in the FWD contains some unsolved uncertainties and highly depends on the initial values, such as the layer thickness [9]. Also, it is difficult to obtain the modulus value, which varies with the depth of the pavement. These shortcomings would reduce the accuracy of the measured modulus results. During the 1980s, Stokoe and his research team developed a new NDT technique to determine the properties of pavements, the Spectral-Analysis-of-Surface-Waves (SASW) method [10,11,12]. The SASW method came from observing how the Rayleigh waves were used in seismology for the Earth’s crust. The researchers found a similar concept could be used for more localized investigations of material stiffness. Over time, several improvements have been made to the SASW method since its inception. In this technique, Rayleigh waves are generated through ground-surface excitation and subsequently captured by a pair of receivers. Based on the Rayleigh wave signal and its dispersion characteristic, the shear wave velocity profile of each layer in a layered structure can be calculated. The modulus of the material varying with depth can also be determined, as the shear wave velocity is an inherent property of the material [13]. Compared to the other NDT methods, the SASW has several advantages: (1) being less dependent on the initial assumed thickness value; (2) providing more comprehensive information, including gradient modulus varying with depth; and (3) assessing the pavement thicknesses. However, the SASW method requires expert knowledge of wave propagation theory to interpret complex results [14], while the FWD method is generally easier to implement.

The SASW method has been successfully used for assessing the bearing capacity of asphalt, subgrade, and base layers over the past decades [15,16,17,18,19,20]. In the evaluation of the subgrade and base layer, the SASW method can evaluate the elastic modulus of rigid and granular aggregate bases [21], determine the seismic parameters of soil stiffness [22], and monitor the seasonal changes in modulus of the base and soil foundation during the whole freeze-thaw cycle [23]. For the asphalt pavement, the SASW method was usually combined with APT testing to monitor the asphalt modulus deterioration trend under controlled traffic and environmental conditions [24,25]. Additionally, as the Rayleigh wave signal can contain the cracking information, it is also possible for the SASW method to study the near-surface damage in the pavement, such as cracks or voids [18,26,27,28,29]. Meanwhile, for the concrete pavement, the SASW method also has the capability to assess the modulus of the concrete pavement [16,30]. Cho and Lin [31] conducted SASW tests on multilayered concrete slabs with a finite thin thickness and found the Rayleigh wave velocity would increase with the increasing age of concrete slabs due to the distinct boundary conditions and reflection at the boundaries. Then, Kim [32] used the SASW method to research the concrete slabs with different boundaries to prove the potential of SASW methods to determine the modulus accurately.

Under these circumstances, considering the practicability and advantages of the SASW method, this research aims to employ the SASW method to comprehensively assess the structural health of concrete pavement, and the modulus is used as the important index to perform the evaluation. In this research project, the asphalt overlay rehabilitation technique will be adopted on three distinct in-service concrete pavements. In order to provide the theoretical basis for the rehabilitation procedure, the SASW tests and FWD tests would simultaneously be conducted to evaluate the pavement condition, including the modulus value and internal distress recognition. Meanwhile, the on-site coring was also conducted at the measurement locations. The cylinder compression strength laboratory tests were performed to calculate the equivalent modulus based on the field cores. This research also shows the potential for using the SASW method to provide insights into the maintenance and rehabilitation of concrete pavements.

2. The SASW Method

In the 1960s, Jones [33] and Vidale [34] proposed frequency-domain methods for analyzing the characteristics of layered structures, where the stiffness of each layer decreased with increasing depth. The dispersion characteristics of surface waves, as a function of frequency or wavelength, were gradually used to evaluate the properties of layered structures. By the 1980s, based on the research of Jones and Vidale, several researchers from the University of Texas at Austin introduced the SASW method, based on the principles of surface wave dispersion, to accurately measure the modulus and thickness of each layer in a pavement system.

The dispersion phenomenon makes the velocity of the surface wave highly dependent on the frequency. The surface wave with different velocities has different frequencies, penetrating the different depths of the layered structure. Moreover, the shear wave velocity can be obtained from the surface wave velocity, and the shear wave velocity represents the properties of the medium itself. Thus, based on the dispersion phenomenon, the inherent characteristics of the material in the pavement can be evaluated according to the surface wave at various velocities.

2.1. The Field Arrangement of SASW Method

The SASW system is composed of several hammers of different sizes, two signal receivers, and a dynamic signal analyzer, as shown in Figure 1. It is primarily used to measure the Rayleigh wave between two receivers at given distances on the ground. The small hammer, serving as the impact source, strikes the ground to generate Rayleigh wave signals within a range of frequencies. The two receivers are vertically placed on either side of the measurement location for receiving and recording the Rayleigh wave signals. The dynamic signal analyzer has a preliminary filtering and fast Fourier transform process for pre-processing the received signals. In this study, the sampling rate is set at 20 microseconds, the total number of data points per sampling is set at 1024, the total duration of time-domain signals is set at 7168 microseconds, and the highest frequency of the signal can reach up to 7 kHz.

During the measurement procedure, the distance between the two receivers should be set equal to the distance between the first receiver and the impact source. At each measurement location, the SASW method requires several repeat experiments by gradually increasing the distance between the receivers. This is because the receiver distance is also related to the measured wavelength of the Rayleigh wave: the longer the distance, the longer the wavelength of the Rayleigh wave that can be collected. Thus, this measurement procedure makes it possible for the acquisition of signals covering different wavelength (frequency) ranges, thereby obtaining the properties of deeper layers.

2.2. The Data Processing of SASW Method

The SASW analysis typically includes three major stages. Firstly, repeated field tests are conducted by changing the different distances of two receivers to collect the field-measured data. Secondly, the filtering process is used to eliminate the unexpected signals that have a low-quality phase spectrum [35], and the representative dispersion curve, i.e., a function of frequency and phase velocity, is built on the basis of the phase difference in the cross-power spectrum obtained by the measured field signals in the frequency domain. Once the two receivers collected the surface wave signal in the time domain, a fast Fourier transform would be performed to obtain the frequency domain data. By extracting the phase difference from the phase information contained in the spectrum signal, the wave velocity and its corresponding frequency can be calculated. Finally, the third and most challenging stage is the inversion analysis.

The purpose of inversion analysis is to obtain the shear wave velocity profile (the plot of wave velocity versus depth) of the measured site from the dispersion curve using some complicated optimization algorithms, such as the maximum likelihood method, the dynamic stiffness matrix method, and the transfer matrix method [36]. The inversion procedure is a nonunique and nonlinear problem that cannot be solved directly. Most of the inversion techniques depend on the iterative calculation from a reasonable initial guess of the stiffness profile to the final solution. After that, the elastic modulus can be calculated from the linear elastic theory due to the minimal strain (less than 0.001%) generated in the measurement [11], as shown in the following equation:

$$E=2·\rho ·V_s^2\left(1+\mu \right)$$

(1)

where $\rho$ represents the density of the pavement material, $\mu$ is the Poisson’s ratio, $V_S$ represents shear wave velocity, and E is the elastic modulus.

3. The Field Testing on Concrete Pavement

This research selected three in-service concrete pavements for field testing, respectively, in Shanghai, Zhejiang, and Jiangxi provinces in China, which were referred to as pavement Sections I, II, and III. The structure of these three pavement sections remained the same, which consisted of a 200-mm-thick concrete layer overlaid on a cement-stabilized crushed stone layer and subgrade soil. Due to the limitations and some unexpected accidences of the field experiments, the SASW method, FWD, and core taking were not tested simultaneously at all measurement locations. The in situ NDT tests and field core test plans are shown in

Table 1. The description of NDT methods and coring tests on three concrete pavements (the “+” represents an experiment conducted, and the “−” symbol means testing is not conducted).

Pavement	Measurement Location	SASW Method	FWD Method	Core Taking
Section I	X1/X2/X3	$+$	$+$	$+$
	Y1/Y2/Y3	$+$	$+$	$+$
	Z1/Z2/Z3	$+$	$-$	$+$
	M	$+$	$-$	$+$
	L	$+$	$-$	$+$
	N	$+$	$-$	$+$
Section II	AA	$+$	$-$	$+$
	BA	$+$	$-$	$+$
	CA	$+$	$-$	$+$
	DA	$+$	$-$	$+$
Section III	JX1-JX10	$+$	$-$	$-$
	A	$+$	$+$	$-$
	B	$+$	$+$	$-$
	C	$+$	$+$	$-$
	D	$+$	$+$	$-$
	E	$+$	$+$	$-$

. In Section I, measurements were taken at 12 designated locations. At half of these sites, the procedures of SASW, FWD, and core extraction were executed, while the remaining six sites underwent only SASW and core extraction. For Section II, all four selected sites were subjected to both SASW and core extraction procedures. In Section III, evaluations were conducted at 15 measurement locations. Of these, five sites were assessed using both SASW and FWD, while a single site was evaluated solely with the SASW method. Notably, no core extractions were conducted in Section III. These locations have been distinctly labeled using different letters, as illustrated in Table 1.

3.1. The Field Measurement of SASW Method

In this research, the SASW device is based on the NDE-360 platform manufactured by Olson Instruments, consisting of a dynamic signal analyzer with anti-aliasing filtering, several hammers, two receivers, and a cable. The SASW field testing is shown in Figure 2. Considering the thickness of the measured concrete pavement, the minimum distance between the two receivers was set at 0.15 m and then increased to 0.3 m, 0.6 m, and 0.9 m. Such multiples increase the receiver’s distance in order to obtain a signal covering a different wavelength range, which can help generate a more robust and accurate dispersion curve. At each receiver distance, the ground will be struck four times with the excitation, and the average value will be calculated as the initial in situ data.

In addition, the forward and reverse measurements were performed for each receiver array, which can eliminate the effects of any unexpected internal phase shifts related to the receiver or signal analyzer [35]. When the field Rayleigh wave signal was organized, the dispersion curve could be constructed, and then the shear wave velocity profile, which varies along the depth, could also be calculated. As the material properties of pavements are evaluated at minor shear strains (less than 0.001%) in the SASW method, the assumption of linear elastic behavior is practical in these materials [19]. Therefore, the elastic modulus of each layer would be determined using the shear wave velocity based on the linear elastic theory.

3.2. The Field Measurement of the FWD Method

As the most popular and commonly used NDT method, FWD is mainly used to collect vertical deflection data when transient loading is applied to the pavement surface. The deflection basin can be drawn from the vertical deflection data measured by each geophone by dropping a weight from a known height onto a loading plate. Then, the modulus of the concrete slab and base of the pavement can be obtained by back-calculating the deflection basin.

Two types of FWD devices were employed in this research, which are trailer-towed FWD and vehicle-mounted FWD, as shown in Figure 3. Both of these two types of FWD instruments consist of one large dynamic falling weight and nine deflection sensors from D0 to D8. The weight of the loading is set at 50 kN, and the distances of each sensor from the D0 sensor are set at 0.2 m, 0.3 m, 0.45 m, 0.6 m, 0.9 m, 1.2 m, 1.5 m, and 1.8 m in sequence. After obtaining the deflection basin at each measurement location on the in-service concrete pavements, the commercial software MODULUS 7.0 would be used to perform back-calculation.

3.3. The Axial Compressive Strength Laboratory Test

The cylindrical concrete core samples with a diameter of 100 mm were taken from the three in-service concrete pavements. Since the concrete slabs already have some damage, the height of the extracted core samples was mostly less than 200 mm. Moreover, the cylindrical specimens cannot be used for the laboratory axial compressive strength tests. Thus, this research cut the field cores into standard specimens with a height of 100 mm to perform the axial compressive strength test. The axial compressive strength test follows the specification of “Testing Methods of Cement and Concrete for Highway Engineering” [37]. Then, the compressive modulus could be calculated according to the empirical conversion formula of the American Concrete Institute (ACI) standard [38], as follows:

$$E_C=3.32{(f_c}^{0.5})+6.9$$

(2)

where the $E_C$ is the compressive modulus, and the $f_c$ is the compressive strength of specimens.

4. Results and Discussion

Three types of modulus data were obtained through field testing, which were SASW modulus, FWD modulus, and axial compressive modulus, respectively. An analytical comparison will be carried out to analyze the results from these diverse measurement types. During the comparison, although the SASW method is capable of deriving the modulus profile as it varies with depth, this research selected to utilize the average modulus of each layer from the SASW results to streamline the comparative analysis of modulus values. Additionally, the performance of in-service concrete pavements and the gradient modulus analysis will also be elucidated.

4.1. The Comparative Analysis of SASW Modulus and Compressive Modulus Results

Theoretically, although the elastic modulus calculated by SASW is much more reliable, it still needs to be compared with the results obtained in laboratory tests to illustrate its persuasiveness.

Table 2. Modulus of elasticity and compressive modules of concrete samples from the SASW method and compressive strength test, respectively.

Pavement Section	Measurement Location	SASW (MPa)	Compressive Modulus (MPa)
Section I	X1	43,291	28,571
	X2	34,075	21,814
	X3	34,958	22,118
	Y1	49,675	30,571
	Y2	46,224	28,773
	Y3	46,996	28,201
	Z1	46,433	26,523
	Z2	47,363	28,302
	Z3	42,591	24,521
	M	45,881	26,715
	L	44,956	26,667
	N	48,131	29,759
Section II	AA	40,861	26,715
	BA	39,218	26,467
	CA	39,131	25,881
	DA	40,254	26,344

summarizes the concrete slab modulus obtained through the SASW method and laboratory testing of field cores at a total of 16 measurement locations in Section I and Section II. It is obvious that the static compressive modulus values are much smaller than those measured by the SASW method. This is due to different ways of loading applications (static vs. dynamic) and different boundary conditions at the measurement locations (restricted vs. unrestricted).

A linear regression analysis of these two types of moduli is performed to obtain the correlation between the SASW modulus and the compressive modulus, as shown in Figure 4. It was found that these two types of moduli are highly correlated, with a correlation coefficient R² of 0.7622 and a Pearson coefficient of 0.8731. These findings align well with prior research that similarly undertook a comparison between the SASW modulus and laboratory compressive modulus, yielding a notable correlation coefficient R² of 0.8553 [39]. Given the reliability of laboratory tests, it can be seen that the SASW method is feasible as a means of detecting the modulus of the concrete layer.

4.2. The Comparative Analysis of SASW Modulus and FWD Modulus

In Section I and Section II, 11 measurement locations were selected to conduct the FWD tests.

Table 3. The summary of concrete modulus from the SASW method and FWD method.

Pavement Section	Measurement Location	SASW (MPa)	FWD (MPa)
Section I	X1	43,291	36,217
	X2	34,075	39,003
	X3	34,958	36,384
	Y1	49,675	22,541
	Y2	46,224	29,460
	Y3	46,996	28,870
Section III	A	47,922	23,277
	B	49,196	34,155
	C	41,020	28,259
	D	44,844	25,993
	E	46,246	28,918

summarizes the concrete layer modulus at the same measurement locations for the SASW and FWD methods. The modulus value shows that the modulus measured by the SASW method is generally larger than the FWD modulus. Considering the sensitivity of modulus is highly related to frequency, the modulus at high frequency is larger than that at low frequency. Thus, the reason for the difference between these two types of moduli is related to the measured frequency. The measured frequency range of the SASW method can reach up to 7 kHz, while the frequency range in FWD measurements is generally between 0 and 60 Hz.

A linear regression analysis is carried out to develop the correlation between the modulus measured by FWD and the modulus obtained from laboratory compression tests. Figure 5 shows the correlation relationship between these two types of moduli, with a correlation coefficient R² of 0.6451, which is less than the correlation coefficient of the SASW method and the compression modulus (0.7622). However, the trends of the correlation relationship between the FWD modulus and the compression modulus are inversely proportional, with a negative Pearson coefficient of −0.8032. The negative coefficient indicates that the modulus from the FWD method is not consistent with the compression modulus. A correlation analysis is also conducted on the SASW modulus and FWD modulus (Figure 6). The correlation coefficient R² between these two types of moduli is only 0.4891, and the Pearson coefficient is also negative (−0.6993), which indicates there is no direct correlation.

4.3. The Modulus of Three In-Service Pavements

Table 4. The summary of concrete modulus from the SASW method.

Pavement Section	Elastic Modulus (MPa)
Section I	Location	X1	X2	X3	Y1	Y2
	Concrete Layer	43,291	34,075	34,958	49,675	46,224
	Subgrade	7135	7825	8081	8490	8137
	Location	Y3	Z1	Z2	Z3	M
	Concrete Layer	46,996	46,433	47,363	42,591	45,881
	Subgrade	8507	8870	7445	7968	8423
	Location	L	N
	Concrete Layer	44,956	48,131
	Subgrade	9005	9170
Section II	Location	AA	BA	CA	DA
	Concrete Layer	40,861	39,218	39,131	40,254
	Subgrade	6501	7096	6640	6992
Section III	Location	JX-1	JX-2	JX-3	JX-4	JX-5
	Concrete Layer	46,352	48,462	47,457	42,912	46,419
	Subgrade	8734	7820	9117	7958	8396
	Location	JX-6	JX-7	JX-8	JX-9	JX-10
	Concrete Layer	45,227	50,514	50,735	55,867	50,737
	Subgrade	8802	7798	6997	7122	7299
	Location	A	B	C	D	E
	Concrete Layer	47,922	49,196	41,020	44,843	46,246
	Subgrade	7519	6315	6855	7481	7213

summarizes the average concrete slab modulus and average subgrade layer modulus at each measurement location of three in-service concrete pavements, as the SASW method can measure the modulus of each layer of the pavement. For a more detailed and clear analysis, the moduli are visualized in Figure 7, where the color blue represents data from Section II, the color red represents data from Section I, and the color yellow represents data from Section III. The circles covering the point data represent the average modulus range of the three concrete pavement sections. Additionally, the horizontal axis of Figure 7 shows the subgrade modulus of the concrete pavements, while the vertical axis shows the concrete modulus of the pavements. From the comparison, it is obvious that both the concrete layer modulus and subgrade layer modulus in Section II are the lowest. The concrete layer modulus at Section III is the highest, while the subgrade modulus at Section I is the highest.

In this research, pavement Section III performs better than the other two pavements, although the initial performance conditions of the three pavements are different. Meanwhile, it is recommended to conduct further detection research on the pavement Section II to monitor the damage degree of the surface and subgrade layer in order to carry out the pavement maintenance in a timely manner. In addition, due to the presence of measurement locations with relatively low concrete layer modulus in Section I, it is also recommended to perform continued monitoring of this pavement section to avoid obvious damage to the pavement, such as surface cracking. The asphalt overlay of these three concrete pavements needs to be carefully designed according to completely different structural conditions.

4.4. The Gradient Modulus Analysis from the SASW Method

Since the SASW method has the ability to provide gradient modulus varying with depth and determine the pavement thicknesses, Figure 8, Figure 9 and Figure 10 select three sets of modulus profiles varying with depth and field cores at locations Y1/Y2/Y4 in Section I from among all the measurement locations. It is worth noting that the extracted core samples, as shown in Figure 8a, Figure 9a and Figure 10a, are placed upside down, whose depth distribution is opposite to the actual depth.

In the analysis of the gradient modulus profile acquired through the SASW method, it can be discerned that the trend of modulus variation across the three measurement locations exhibits coherence (Figure 8a, Figure 9a and Figure 10a). Within the depth extending from 150 mm to 200 mm, there is an obvious decrease in modulus. Following this zone, a stabilization of the modulus is observed after a depth of more than 200 mm, indicating a homogenous material characteristic in this specific depth interval. This gradient modulus trend is consistent with the actual situation, as mentioned in the previous Section 3.3. Although the original structural design of the concrete pavement showed a 200-mm-thick concrete layer over cement-stabilized crushed stone and subgrade soil, the heights of the retrieved core samples were found to be under 200 mm due to the inherent damages within the observed concrete slabs. These inherent distresses, such as cracking and delamination within the depth of about 150 mm to 200 mm, affect the integrity and performance of core samples and are then reflected by the modulus value. After the depth of 200 mm, the modulus base layer has few variations, which may indicate there are no obvious damages within the base layer.

It is reasonable that the gradient modulus profile measured by the SASW method could make inherent distress recognition possible. The modulus distribution has the capability to determine the location of the inherent distress based on the region where the modulus suddenly decreases. After obtaining a comprehensive evaluation of concrete pavement condition, the design of overlay asphalt thickness and material would be more targeted and suitable for each different concrete pavement.

5. Conclusions and Future Work

This research assessed the modulus of three in-service concrete pavements using the SASW method and compared the corresponding modulus measured by FWD with a compressive strength laboratory test. Based on the modulus analysis, the theoretical basis for asphalt overlay schemes on concrete pavements could also be provided. The comprehensive evaluation of concrete pavement condition, including the modulus value and internal distress recognition, has the capability to assist in determining the design of overlay asphalt thickness and material.

The conclusions are summarized below:

(1) The SASW method can accurately obtain the elastic modulus of the concrete slab and base layer of the concrete pavements, which can serve as an effective, reliable, and high-precision NDT method for assessing the overall modulus of concrete pavements throughout their entire service life.

(2) Compared with the concrete slab modulus measured by FWD, the concrete slab modulus measured by the SASW method was much closer to the axial compressive modulus measured by in situ cores and had a high correlation.

(3) Among the three in-service concrete pavements, pavement Section III performed the best in terms of the concrete slab and base layer. Section II of the pavement needs further damage investigation for both the lowest concrete and base layer. Meanwhile, because the pavement in Section I has a relatively low concrete slab modulus compared to Section III, it was recommended to perform more field NDT testing to determine a more suitable and targeted asphalt overlay scheme.

(4) It is reasonable that the gradient modulus profile measured by the SASW method could make the inherent distress recognition possible. The modulus distribution has the capability to determine the location of the inherent distress based on the region where the modulus suddenly decreases.

Although the SASW method has some advantages in evaluating the concrete pavement condition, it still has several drawbacks, such as the high requirements for field testing procedures and manpower engagement, culminating in a complex and time-intensive measurement procedure. In these cases, it is considered necessary to develop a new methodology or improve the measurement process to enhance the efficiency of field testing in future research. Thus, it is anticipated that the comprehensive assessment of pavement conditions might become significantly streamlined and much more accurate.