Quantitative Assessments of Crack Sealing Benefits by 3D Laser Technology

Abstract

Crack sealing is one of the most commonly used methods to preserve asphalt pavements. However, quantification of crack sealing benefits (or the long-term delaying effects of crack sealing on crack propagation) remains unavailable because field crack lengths could not be measured accurately and efficiently. In this study, 3D laser technology is proposed to measure and compare the growth of crack lengths between sealed and non-sealed pavement sections and, for the first time, to accurately and efficiently quantify the crack sealing benefits. To validate the proposed method and find adequate treatment timing (or conditions), nine field sites in Georgia, U.S., with different pavement pre-treatment conditions and roadway environmental factors were monitored over 3 years from December 2016 to September 2019. The study results showed that crack sealing can retard crack growth by 40%–128%, and such delaying effects are more significant under better pavement pre-treatment conditions. The findings suggest that transportation agencies can prolong the service life of pavements by applying crack sealing before the pavement condition becomes poor. In addition, this work has been proved to be very valuable for transportation agencies to determine the best timing and treatment criteria for crack sealing.

Crack sealing/filling is the most commonly used method to preserve asphalt pavements, and it has been specified by the Departments of Transportation (DOTs) in many U.S. states and regions. Decker conducted a survey in 2014, concluding that DOTs of different sizes in the U.S. have annually spent from $100,000 to $10,000,000 on crack sealing/filling ( 1 ). In the 2011 fiscal year, Indiana DOT performed crack sealing/filling on 5,500 lane miles of roads (out of 29,600 total lane miles of roads they managed) at a cost of more than $4,300,000 ( 2 , 3 ). Moreover, Alaska DOT spent more than $1,000,000 per year on crack sealing/filling ( 4 ). However, because of limited maintenance budgets and rising costs for labor and material, efficient crack sealing/filling becomes crucial to extend the service life of a pavement.

Different transportation agencies have slightly varied definitions of crack sealing/filling. In Decker’s survey, 62% of the 157 respondents made no distinction between crack sealing and crack filling ( 1 ). Therefore, in this paper, “crack sealing” refers to all types of crack sealing/filling. Furthermore, the crack treatments in this study followed the “crack sealing” practices of Georgia DOT (GDOT), in which “Type S” high-quality hot-poured asphalt-rubber sealant is used without routing ( 5 ).

Although many previous studies have been conducted to evaluate the field performance of crack sealing, they cannot measure the crack sealing benefits objectively and quantitatively enough for benefit-cost analysis and determination of the optimal timing for crack sealing. Two major methods have been proposed in previous studies, and the first one is to evaluate the durability life of the sealant as a representative of the field performance of the crack sealing ( 6 – 12 ). However, the durability life can only reflect the construction quality of the crack sealing; it is not capable of demonstrating the actual delaying effect. In the second method, the performance of crack sealing is assessed by an extended pavement life, which is measured by comparing the deterioration of composite ratings (e.g., pavement condition index) between the sealed and non-sealed sections after crack sealing ( 13 – 15 ). However, the composite ratings are composed of pavement distresses other than cracking, such as rutting, raveling, and roughness. These distresses are not influenced directly by crack sealing. Meanwhile, it is noteworthy that the composite ratings in these previous studies were manually collected without clarifying the crack features to quantify the crack sealing benefits. In a word, a quantitative method to measure crack sealing benefits based on the delaying effects of crack sealing on crack propagation remains unavailable.

On the other hand, 3D laser technology has great potential to tackle the problem described above, as it collects high-resolution 2D intensity images and 3D range images simultaneously, enabling transportation agencies to detect and measure pavement cracking (including sealed cracks) accurately and rapidly with a high granularity. Recently, 3D laser technology has gradually become a mainstream technology for collecting pavement surface images and detecting pavement distresses. A survey in 2017 showed 18 U.S. states have been using a 3D-automated data collection system, and another 17 states declared their plans to use similar systems within 2 years ( 16 ). Cracking, rutting, concrete joint and its faulting, raveling, and potholes have been successfully detected from 2D and 3D pavement images with advanced computer vision and deep learning technologies ( 17 – 25 ). The pavement distresses extracted with high granularity are then used to support pavement management systems (PMS) so that the PMS can apply the right roadway treatment at the right location at the right time. Many implementations of 3D laser technology on PMS have been studied, such as crack deterioration analysis, quality control of micro-milled pavement surface texture at the project level, automated raveling classifications, the determination of optimal treatment timing with new indicators of pavement performances, deep patching segmentation and selection with automatic crack classifications, and automated classification of jointed plain concrete pavement conditions ( 23 , 26 – 30 ). Although the crack features of high granularity (e.g., crack length, width, density, direction, and location) collected by 3D laser technology have been used to measure crack growth and analyze pavement deterioration, they have not yet been fully studied and implemented to quantify the crack sealing benefits ( 31 ).

The objectives of this study are: (1) to propose a quantitative method to measure crack sealing benefits considering the delaying effect of crack sealing on crack propagation; and (2) to study the adequate treatment timing (or conditions) by monitoring and comparing the long-term crack sealing benefits in different pavement pre-treatment conditions and roadway environmental factors.

This paper is organized as follows. This section has introduced the background and research objectives. The next section presents the literature review. The section after that presents the proposed methodology for quantifying crack sealing benefits. The following section presents the research results. The penultimate section presents the analysis and discussions. The final section presents conclusions and recommendations.

Literature Review

In this section, the definitions of crack sealing/filling among states, and two widely-used evaluation methods for crack sealing performances are summarized.

Definition of Crack Sealing/Filling

The definitions of crack sealing/filling vary among transportation agencies. One definition strategy distinguishes crack sealing and crack filling by the routing operations in which a router is used to create a reservoir and enhance the adhesion and cohesion of the sealants ( 7 , 32 ). In crack sealing (or rout-and-seal), the reservoir is created before sealing. On the other hand, routing is not conducted in crack filling (or clean-and-seal), and the pavement is only cleaned before sealing. The second definition strategy differentiates crack sealing and crack filling by the sealant quality. Smith and Romine defined crack sealing as a process in which specialized treatment materials are placed above or into the working cracks (cracks with a width > 3 mm), while in crack filling, only ordinary treatment materials are filled into non-working cracks ( 8 ). Barman et al. stated that, in Minnesota, crack sealing requires high-quality sealant materials of “Type 2” (50% extension at −20°F) as specified by ASTM D6690, and these materials exhibit very promising bonding features for the working cracks ( 7 , 33 ). However, crack filling requires low-quality crack sealants of “Type 1” (50% extension at 0°F), which are applied on non-working cracks. Mazumder et al. concluded that, in most U.S. states, routing is not performed before crack sealing/filling, which is probably because of the higher costs as a result of extra labor and equipment ( 9 ). Nevertheless, routing would generally enable longer durability for the pavements.

Evaluate Crack Sealing Performance by Assessing Crack Sealant Durability

“Durability” refers to the service life of the sealant, which can be used to assess the performance of the crack sealing. Other terms, such as “performance,”“effectiveness,” and “service life,” are also used to describe the durability of crack sealants ( 8 , 9 ). Smith and Romine suggested measuring the sealant performance by summing the lengths of failed segments and dividing the sum by the total length of the treated cracks ( 8 ). Based on multiple field inspections at different times after the treatment, a graph can be drawn to reflect the treatment effectiveness over time. An effectiveness of 50% is used as a threshold to define crack sealing failure. Based on this concept, the American Association of State Highway and Transportation Officials (AASHTO) PP20-95 standardized the performance evaluation of crack sealing treatments on asphalt pavements ( 10 ). Following the AASHTO standard, Yildirim et al., and Zinke and Mahoney compared the performances of hot- and cold-pour crack sealing with field test data ( 11 , 12 ). Mazumder et al. compared the durability of crack sealants in crack sealing/filling by measuring the percentage of sealant failure among all the treatment sites ( 9 ). It is noteworthy that the failed crack lengths were measured by long rulers or a measuring wheel in the field ( 12 ).

Al-Qadi et al. developed a weighted rating system known as the performance index (PI) to evaluate the sealant damages following the aforementioned methods ( 6 , 8 ). PI was calculated as: $PI = 100 - (AC + PAC^{*} 0.5)$ ,

where

AC is the percentage of full adhesive or cohesive failures; and

PAC is the percentage of partial adhesive or cohesive failures.

Subsequently, Barman et al. modified the equation to evaluate the effectiveness of crack sealing by incorporating more sealant distress types, including adhesion loss, cohesion loss, spalling, pull-out failure, and stone intrusion ( 7 ). Their field test results showed that, if the PI threshold is set as 50%, crack sealing has an approximate service life of 3–4 years.

Nevertheless, the durability of crack sealants can only indicate the quality of the crack sealing operation. It cannot reveal the actual benefits of crack sealing on delaying crack propagation.

Evaluate Crack Sealing Performance by Its Benefits

Three methods have been proposed to measure the benefits of crack sealing between the sealed and non-sealed roads. The methods are based on pavement service life (PSL), pavement condition ratings (PCR) or pavement roughness (International Roughness Index [IRI]), and delayed growth of crack lengths.

For the PSL-based method, Rajagopal compared the deterioration trends between sealed and non-sealed pavements with linear regression, and the field tests revealed an extension of PSL by 0–2 years across various surface types after crack sealing ( 13 ). Vargas-Nordcbeck and Jalali used survival analysis to determine the extension of PSL ( 14 ). After more than 6 years of field monitoring, they concluded that the benefit was 4.6–7.3 years for “fair” pavements and 1.1–2.1 years for “poor” ones. Hajj et al. measured the present serviceability index (PSI) before and after sealing to determine the extension of PSL ( 15 ). They found 71% of the crack-sealed pavements showed a higher PSI, and the extension of PSL was 1.5–4 years. However, composite ratings are not favorable to reflect the crack sealing benefits because other pavement distresses (e.g., rutting and raveling) are also involved.

For the PCR- or IRI-based method, Rajagopal measured the average PCR gains over 5 years and revealed a 3.6%–5.8% increase in the average PCR across different types of pavements ( 13 ). Lee et al. used IRI to evaluate the crack sealing performances and reported that, in the crack-sealed pavements, the average IRI showed a decrease of 1.13 in./mi compared with the untreated ones ( 34 ). Lu and Tolliver reported that crack sealing has short-term effects on pavement performance, which are reflected by an IRI as low as 28 in./mi, according to the Long-Term Pavement Performance (LTPP) data ( 35 ). Other studies found no significant differences in IRI between sealed and non-sealed pavements ( 36 , 37 ). However, crack sealing is conducted to delay the crack growth, so measuring the benefits of crack sealing based on PCR or IRI is too indirect and inefficient.

In the last method, the delaying effect of crack sealing on crack growth is reflected directly. Lee et al. compared the crack growths of sealed and non-sealed pavements over a period after crack sealing ( 34 ). They used pavement surface images to give qualitative proofs of the benefits of crack sealing. However, they failed to measure the benefits of crack sealing when the pre-treatment crack lengths are different among test sites, as they used the absolute crack lengths for comparison. With 2 years of observation, CRAFCO Inc. said they have found 75% less cracking in the crack-sealed pavements than in those without any treatment, but the details of this discovery remain a mystery ( 38 ). Nevertheless, the crack growth rates of the sealed and non-sealed sections are compared in the last method, which is a very straightforward and effective way to show the benefits of crack sealing, especially when the crack lengths can be monitored accurately and efficiently for a long time. To the best of the authors’ knowledge, no articles have been published to illustrate the details of measuring the delayed growth of crack length over time, which is, in turn, used as the foundation for quantifying the benefits of crack sealing. In conclusion, in this study, 3D laser technology is used to monitor the long-term growth of crack lengths to directly quantify crack sealing benefits for the first time.

Methodology

This section presents the proposed methodology that quantifies the crack sealing benefits on field sites by measuring the delaying effect of crack sealing on crack length growth; it uses 3D pavement data collected via 3D laser technology. In addition, to find the best treatment timing (or conditions), field test sites under different pavement pre-treatment conditions and roadway environmental factors were selected, and their long-term crack sealing benefits were analyzed.

Part 1: Field Test

Selection of Field Test Sites

To study what constitutes adequate crack sealing timing, the GaTech research team conducted field tests at nine different locations (six in Hawkinsville in southern Georgia [GA] and three in Covington in central GA), covering different pavement pre-treatment conditions and different roadway environmental factors (e.g., pavement thickness, traffic volume, and truck percentage). Figure 1 shows the locations of the field tests. It should be noted that initially ten test sites were selected, but Site 7 was accidently resurfaced several months after crack sealing was applied, so it was excluded in the following study.

Figure 1.

Location of test sites: (a) Sites 1 to 6 in Hawkinsville, Southern Georgia (GA) and (b) Sites 8 to 10 in Covington, Central GA.

Design of the Comparative Test (Sealed versus Non-Sealed)

The comparative test was designed to quantify the crack sealing benefits at each test site. Each test site was designed with two sealed sections and one non-sealed section. Each sealed or non-sealed section was 500 ft long and was located close to other sections in the same lane.

Two different test scenarios were considered. The first was a “one-time sealing” scenario, in which two sealed sections were sealed simultaneously in December 2016. The second was a “multi-time sealing” scenario in which one of the sealed sections was sealed in December 2016, and the other was sealed in February 2018. This made it possible to directly observe the slow-down effect because the later sealed section had been monitored for both the non-sealed period (Dec. 2016–Feb. 2018) and the sealed period (Feb. 2018–Dec. 2019). Figure 2 shows the layout of the two scenarios in this test.

Figure 2.

The layout of two scenarios of comparative test: (a) one-time sealing and (b) multi-time sealing.

Crack Sealing Field Operation

The first crack sealing applications were conducted by GDOT in December 2016, and the second time was in February 2018. “Type S” asphalt-rubber material was used, which is a hot-applied thermoplastic material that can seep in and fill small cracks because of its very low viscosity ( 5 ). There is no routing and cutting before the crack sealing. The cracks were cleaned first using compressed air, as shown in Figure 3a. A hot-pour sealing method was used, as shown in Figure 3b.

Figure 3.

Crack sealing operation by Georgia Department of Transportation (GDOT): (a) crack cleaning and (b) crack sealing.

Pavement Image Data Collection

In this study, the Georgia Tech sensing vehicle (GTSV) was used to collect pavement image data every 3 months for 3 years from December 2016 to September 2019. The high-resolution 2D intensity image and 3D range image were collected simultaneously by two line-laser-based scanning sensors mounted at the rear of the GTSV, as shown in Figure 4a. The maximum data collection speed of GTSV is 100 km/h. Each frame of 3D surface point cloud data consists of 1,000 points (driving direction) by 4,160 (transverse direction) points, with an interval of 5 mm in the driving direction and 1 mm in the transverse direction. The range value is stored at each point with an accuracy of 0.5 mm. Each pavement image covers an area of 5 m in the driving direction and 4 m in the transverse direction with a resolution of 5,000 × 4,160 pixels. Figure 4, b and c , respectively, show an example of the 2D intensity and 3D range images collected at the same location in the real-world. From the 2D intensity image, the lane markings are white, while the asphalt pavement surface is grey or black. This is because white in the 2D intensity image represents a higher reflectivity on the surface of the object. From the 3D range image, the cracks are black, while the pavement surface is grey. This is because the black in the 3D range image represents the objective surface that is farther than the other areas. In this study, 2D intensity image data and 3D range data are used complementarily. The 2D intensive images were mainly used to detect sealed cracks, and the 3D range images were mainly used to detect the non-sealed cracks with crack width greater than 2 mm.

Figure 4.

Georgia Tech sensing vehicle (GTSV) and examples of 2D and 3D pavement surface images: (a) GTSV, (b) 2D intensity image, and (c) 3D range image.

Part 2: Pre-treatment Conditions and Roadway Factors Collection

In this study, the pavement pre-treatment conditions are expressed by the Computerized Pavement Condition Evaluation System (COPACES) rating. COPACES is a software tool that has been used by GDOT for statewide pavement condition survey in accordance with GDOT’s Pavement Condition Evaluation System (PACES) since the late 1990s ( 39 – 42 ). The pre-treatment COPACES rating data was acquired from the historical COPACES database of GDOT.

The roadway environmental factors data used in this study include traffic volume and pavement thickness. The traffic volume data can be represented by: the annual average daily traffic (AADT); the percentage of trucks; and the annual average daily truck traffic (AADTT); the pavement thickness data was collected by taking cores at each test site. The collected cores show that there are no pavement structure deficiencies at the selected test sites. Table 1 summarizes the information of the pavement pre-treatment conditions and roadway environmental factors.

Table 1.

Summary of Pre-treatment Conditions and Roadway Environmental Factors

Site number	Road name	Pavement structure	Pavement thickness (inch)	Traffic	AADT (2018)	Truck percentage	AADTT* (2018)	Pavement condition	Pre-treatment COPACES rating	Design of the comparative test
1	GA 26	Composite	9.5	High	4,430	26	1,148	Poor	66	One-time
2	GA 26	Composite	10	High	4,480	24	959	Good	95	Multi-time
3	GA 230	Thin AC layer	2.5	Low	1,020	13	128	Poor	69	One-time
4	US 341	Full depth	6.5	Medium	3,890	17	662	Good	93	Multi-time
5	GA 230	Thin AC layer	8	Low	1,030	14	133	Good	98	Multi-time
6	US 341	Full depth	6.5	High	5,260	14	722	Poor	69	One-time
8	GA 212	Thicker AC layer	8	High	7,270	6	349	Good	79	One-time
9	GA 212	Thicker AC layer	8	High	12,900	4	488	Medium	85	One-time
10	GA 212	Thicker AC layer	9	High	8,530	3	166	Poor	82	One-time

Note: AADT = annual average daily traffic; AADTT = annual average daily truck traffic; AC = Asphalt Concrete; COPACES = Computerized Pavement Condition Evaluation System.

Part 3: Pavement Image Data Processing

Four steps are taken to convert the 3D pavement surface image data into crack length information, which are: (1) automatic lane marking detection and manual adjustment; (2) multiple-timestamp pavement data registration; (3) semi-automatic crack map digitization; and (4) crack length computation.

Step 1: Lane Marking Detection and Modification

The lane marking detection is first processed automatically using LcmsRoadInspect software developed by the Pavemetrics Company. However, in some complex road conditions, such as a worn lane marking or at a road exit, the lane marking detection is usually inaccurate. Therefore, visual inspection and manual modification of data are essential to ensure the accuracy of the lane marking position.

Moreover, the correct lane marking position is of importance for an accurate crack length computation because the lane marking position is used to confine the crack length counting region and to avoid other cracks located out of the lane, such as construction joints. Furthermore, the lane marking position is also used to conduct the multiple-timestamp data registration for the consistency of crack length growth comparison.

Step 2: Multiple-Timestamp Pavement Data Registration

The purpose of this step is to determine the region of interest (ROI) with a consistent boundary and area for the computation and comparison of crack length at different timestamps. Normally, the pavement image collecting system only covers the width range of one lane when the vehicle is driving in the middle of that lane. In actual data collection, however, the vehicles wander differently in surveys because of the different driving behaviors of different drivers, which in turn affects the coverage area of different surveys. To solve this problem, this project adopted a semi-automatic registration method to compute the overlapping area among different surveys at a certain location for a fair and consistent comparison. This multiple-timestamp data registration method was previously developed by the author and applied to crack deterioration analysis ( 27 ).

Step 3: Semi-Automatic Digitization of Crack Map

In this study, the non-sealed crack was digitized by a semi-automatic crack digitization tool based on the minimal path algorithm developed by the GaTech research team ( 43 , 44 ). Compared with the fully automatic crack detection algorithms, this semi-automatic method exhibits higher accuracy and lower sensitivity when the pavement image quality is slightly different in different runs of data collection. Figure 5a shows the digitized non-sealed crack overlay. The sealed crack digitization was manually drawn with a mouse using the crack digitization tool. Figure 5b shows the digitized sealed crack overlay.

Figure 5.

Digitized crack overlay: (a) non-sealed crack and (b) sealed crack.

Step 4: Crack Length Computation

The crack map, generated from the previous step, is stored in an XML file using the x, y coordinates of the nodes. By connecting the nodes and accumulating the distances between every two nodes connected, the crack length of each crack segment can be calculated. Then, the total crack length in each of the 500 ft test sections can be aggregated. A MATLAB tool was developed by the GaTech research team to batch process these XML files and summarize the information into readable tables.

Part 4: Quantifying of Crack Sealing Benefits

After the crack length has been accurately and effectively extracted, the crack sealing benefits ( $CSB$ ) can be quantified by comparing the difference of long-term crack length growth between the sealed section and the non-sealed section. It can be formulated as follows:

C S B = Δ C L {(%)}_{N o n - S e a l e d} - Δ C L {(%)}_{S e a l e d}

(1)

where

$Δ C L {(%)}_{N o n - S e a l e d}$ denotes the percentage of the crack length growth in non-sealed test section; and

$Δ C L {(%)}_{S e a l e d}$ denotes the percentage of the crack length growth in sealed test section.

Then, the percentage crack length growth ( $Δ CL$ ) in the testing period for either sealed or non-sealed section can be calculated using the following:

Δ C L (%) = \frac{C L_{t 2} - C L_{t 1}}{C L_{t 1}}

(2)

where

$C L_{t 2}$ refers to the crack length at the end of the test period; and

$C L_{t 1}$ refers to the crack length at the beginning of the test period.

In addition, the actual crack length growth ( $Δ CL$ ), in meters, as the most straightforward way to observe the crack length growth, has been computed using the following equation:

Δ CL = C L_{t 2} - C L_{t 1}

(3)

Results

In this section, the crack length growth over 3 years was calculated and plotted for both sealed and non-sealed sections. The crack length growth at the test sites was examined to evaluate the crack sealing benefits (or the delaying effect of crack sealing on crack length growth). As mentioned before, two ways were used in this study to show the crack length growth. One was to plot the actual crack length (in meters) over time, as shown in Figure 6a. The other was to plot the percentage of crack length growth over time, as shown in Figure 6b. The percentage of crack length growth is calculated using Equation 2, while the actual crack length growth is calculated using Equation 3. The purpose of using the percentage crack length growth is to make a fair comparison when test sites have different pre-treatment crack lengths.

Figure 6.

Crack length growth plotting of Site 1 (one-time sealing): (a) actual crack length growth, and (b) percentage of crack length growth.

Site 1 is an example of a one-time sealing scenario, as shown in Figure 6. Since two of the sealed sections were sealed simultaneously at the beginning of the test, the results showed that the crack growth rates on both two sealed sections was low, while, on the contrary, the crack growth rate of the non-sealed section was high.

Site 5 is an example of a multi-time sealing scenario, as shown in Figure 7. At this site, the two sealed sections were sealed at different times, with Section 1 sealed at the beginning of the test in December 2016 and Section 2 sealed at the midterm of the test in February 2018. The results showed that the crack growth rate on the sealed Section 1 remained low, while the crack growth rate on the sealed Section 2 was first high before the sealing (before February 2018, the 16th month of data collection) and then dropped much lower (slowed down) after the sealing application.

Figure 7.

Crack length growth plotting of Site 5 (multi-time sealing): (a) actual crack length growth, and (b) percentage of crack length growth.

Instead of plotting the crack growth for all sites, crack sealing benefits were calculated based on Equation 1 and summarized for all sites in Table 2; additional information, such as pavement pre-treatment conditions, roadway factors, actual crack length growth, and percentage of crack length growth, were also included to analyze the adequate crack sealing timing (or conditions). It is noteworthy that two sealed sections in the one-time sealing scenario were averaged as one value. For the multi-time sealing scenario, only the initially sealed section was used.

Table 2.

Summary of Results

Site number	Pre-treatment COPACES rating	Pavement thickness (inch)	Annual average daily traffic (AADT) (2018)	Truck (%)	Annual average daily truck traffic (AADTT) (2018)	Non-sealed section			Sealed section			Crack sealing benefit (%)
Site number	Pre-treatment COPACES rating	Pavement thickness (inch)	Annual average daily traffic (AADT) (2018)	Truck (%)	Annual average daily truck traffic (AADTT) (2018)	Initial crack length (m)	Crack length growth (m)	Percentage crack length growth	Initial crack length (m)	Crack length growth (m)	Percentage crack length growth	Crack sealing benefit (%)
1	66	9.5	4,430	26	1,148	566	243	43	653	22	3	40
2*	95	10	4,480	24	959	80	88	111	60	6	10	101
3	69	2.5	1,020	13	128	237	124	52	403	19	5	48
4*	93	6.5	3,890	17	662	102	134	131	321	23	7	124
5*	98	8	1,030	14	133	66	68	102	81	17	21	82
6	69	6.5	5,260	14	722	153	83	54	178	18	10	44
8	79	8	7,270	6	349	109	83	76	204	4	2	74
9	85	8	12,900	4	488	151	85	56	214	10	5	52
10	82	9	8,530	3	166	134	107	80	366	8	2	78

Note: AADT = annual average daily traffic; AADTT = annual average daily truck traffic; COPACES = Computerized Pavement Condition Evaluation System.

Red indicates COPACES ≤ 70, yellow indicates 70 < COPACES ≤ 90, and green indicates COPACES > 90.

multi-time sealing scenarios.

Analysis and Discussion

Discussion on Crack Sealing Benefits

The GaTech research team found obvious crack sealing benefits in the first 3 years after crack sealing on all selected test sites, as shown in Table 2. Here are some key findings:

For all sites, the percentage of crack length growth in the non-sealed control section is significantly greater than that in the sealed test section. The minimum crack sealing benefit is 40% in Site 1, and the maximum crack sealing benefit is 124% in Site 4. The test outcomes suggest that crack sealing is very effective in delaying the growth of crack length.

Either the actual crack growth or the percentage of crack growth on sealed sections was significantly low in 3 years. The maximum actual crack growth on the sealed section is 23 m on Site 4, which is equivalent to 7% of the crack length growth at the initial crack length of 321 m. The maximum percentage of crack length growth on sealed sections is 21% in Site 5, which is equivalent to a crack growth of 17 m over an initial crack length of 81 m.

Field test results show that the crack sealing benefits are significant (at least 40%) in retarding crack growth for pavement conditions with different pavement pre-treatment conditions (COPACES ratings ranging from 66 to 98), different pavement thicknesses (ranging from 2.5 to 10 in.), and different traffic volumes (AADT ranges from 1,030 to 12,900; truck percent ranges from 3% to 26%; AADTT ranges from 128 to 1,148).

Analysis and Discussion of Adequate Crack Sealing Timing

Pavement Pre-treatment Conditions

The pavement pre-treatment conditions were measured by the COPACES rating. The correlation analysis shows the trend in Figure 8a with a coefficient of determination (R²) of 0.664, which indicates that better pre-treatment conditions with a higher COPACES rating will lead to higher crack sealing benefits (if the impact of thickness and traffic is ignored). The breakdown analysis of the crack sealing benefits under different pre-treatment conditions is as follows:

With COPACES rating range from 93 to 98, the crack sealing benefits are high (ranging from 82% to 124%).

With COPACES rating range from 79 to 85, the crack sealing benefits are moderate (ranging from 52% to 74%).

With COPACES rating range from 66 to 69, the crack sealing benefits are low (ranging from 40% to 48%).

Figure 8.

Correlation analysis of pre-treatment Computerized Pavement Condition Evaluation System (COPACES) rating and crack sealing benefit: (a) correlation analysis of COPACES and (b) summary of variables and benefit.

Traffic Volume

Figure 9 shows the correlation analysis between traffic volume and crack sealing benefits. The results show that neither AADT nor AADTT correlates with the crack sealing benefits because the coefficients of determination (R²) are 0.026 and 0.0005, respectively.

Figure 9.

Correlation analysis of traffic volume and crack sealing benefit: (a) annual average daily traffic (AADT) versus crack sealing benefits and (b) annual average daily truck traffic (AADTT) versus crack sealing benefits.Red indicates COPACES < 70, yellow indicates 70 ≤ COPACES ≤ 90, and green indicates COPACES > 90.

Pavement Thickness

Figure 10 shows the correlation analysis between pavement thickness and crack sealing benefits. No correlation between pavement thickness and crack sealing benefits was observed. The coefficient of determination (R²) is 0.0446.

Figure 10.

Correlation analysis of pavement thickness and crack sealing benefit.Red indicates COPACES < 70, yellow indicates 70 ≤ COPACES ≤ 90, and green indicates COPACES > 90.

Pre-Treatment Crack Characteristics

In addition to the analysis of the aforementioned three pavement condition variables, the impact of pre-treatment crack characteristics (e.g., load crack [LC] and block/transverse [B/T] crack) on the crack sealing benefits was also analyzed. Table 3 summarizes the pre-treatment crack characteristics based on the visual survey results of collected pavement images. The characteristics of the cracks were described using three severity levels of LC and two severity levels of B/T crack, which followed the definition in GDOT’s COPACES manual ( 39 – 42 ). In this table, the percentage number for each category of cracking shows the proportion of the extended cracking length to the total length of the test section (500 ft) before the treatment. Besides, the crack sealing benefits and the pre-treatment COPACES rating were combined to analyze the impact of pavement pre-treatment conditions on crack sealing benefits. The discussion is as follows:

Poor conditioned pavement on Site 1 with 45% Level-1 LC, 45% Level-2 LC, 5% Level-3 LC, and 80% Level-2 B/T can have a 40% crack sealing benefit. This result shows that Site 1, which has the worst pavement pre-treatment condition with a very low COPACES rating of 66, can still benefit from the crack sealing. Its crack growth on the sealed section was reduced by 40% compared with the section that was not sealed.

Crack sealing benefits are high (82%–124%) when there is only small LC (0%–10%); see Sites 2, 4, and 5.

Crack sealing benefits are relatively low (40%–48%) when there is large and severe LC (more than 70% Level-1 or Level-2 LC). In this case, 20% to 80% Level-2 B/T usually occurs simultaneously.

The occurrence of Level-1 B/T has less negative impact on the crack sealing benefits than LC and Level-2 B/T.

Table 3.

Summary of the Impact of Pre-Treatment Crack Pattern on Crack Sealing Benefit

Site number	Pre-treatment COPACES rating	Extend length percentage of cracks by category					Crack sealing benefit (%)
		Wheel path load crack (LC)			Block/transverse (B/T) crack
		Level 1	Level 2	Level 3	Level 1	Level 2
1	66	45	45	5	0	80	40
2	95	5	0	0	30	0	101
3	69	60	20	0	10	50	48
4	93	10	0	0	50	0	124
5	98	10	0	0	20	0	82
6	69	60	10	0	40	20	44
8	79	10	0	0	50	0	74
9	85	20	0	0	60	0	52
10	82	20	0	0	30	0	78

Note: COPACES = Computerized Pavement Condition Evaluation System.

Conclusions and Recommendations

According to the analysis of the field test results over the past 3 years, the conclusions are summarized below:

Crack sealing can effectively delay crack growth by 40%–128% when pre-treatment COPACES rating ranges from 66 to 98.

Crack sealing benefits, as a delaying effect, are more significant when applying crack sealing to the pavements with better pre-treatment conditions. This finding suggests that transportation agencies can broaden the upper limit of the crack sealing timing criteria to prolong the life of pavements under healthy conditions rather than under poor conditions.

There is no clear trend of the impact of traffic volume and pavement thickness on crack sealing benefits.

Analysis of the impact of pre-treatment crack characteristics on crack sealing benefits shows that the occurrence of more severe (either longer-extent or higher-level) load cracking or more Level-2 B/T cracking will lead to lower crack sealing benefits. Besides, different extents of Level-1 B/T cracking will have obtained high crack sealing benefits.

Based on the current study, recommendations for future studies are as follows:

Continue to monitor the crack growth on the test sites to study the long-term performance (e.g., 5 or more years) of crack sealing.

Continue to monitor the crack growth on the comparative test sections to compare the crack propagation of the sections when crack sealing is applied at different timings.

Quantify the crack sealing benefits by measuring the prolonged pavement life based on the overall rating, including cracking, rutting, raveling, roughness, friction, and other conditions.

Use the actual crack sealing benefits under different crack characteristics with their estimated costs to develop a benefit-cost model for selecting crack sealing projects.

Investigate the effects of crack sealing on pavement quality, such as friction and roughness, which may limit the earliest treatment timing and maximum crack sealing area.

Extend this study to more test sites and a wider range of traffic levels and pavement thicknesses to better study their relationship with the crack sealing benefits.

Collect temperature data to study the impact of pavement surface temperature on crack length measurement, because the measured crack length may be affected by potential temperature-induced self-healing.

Footnotes

Acknowledgements

The authors would like to thank Ms. Ernay Robinson, Mr. Sam Wheeler, Mr. David Sparks, and Mr. Rodney Way from GDOT’s Office of Maintenance for their support of field crack sealing operation and data collection. The authors would also like to thank Mr. Binh Bui (former GDOT engineer) and Mr. Brennan Roney from GDOT’s Office of Performance-based Management and Research for their assistance on this research project. The authors also would like to thank Dr. Hasan Ozer for sharing his crack sealing and filling references.

Author Contributions

The authors confirm contribution to the paper as follows: study conception and design: Z. Wang, Y. Tsai; data collection: X. Zhang, Z. Yang, Z. Wang; analysis and interpretation of results: Z. Yang, X. Zhang, Y. Tsai, Z. Wang; draft manuscript preparation: Z. Yang, Y. Tsai. All authors reviewed the results and approved the final version of the manuscript.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study presented in this paper is sponsored by the Georgia Department of Transportation (GDOT) research project 14-06.

ORCID iDs

Zhongyu Yang

Xinyi Zhang

Yichang (James) Tsai

Zhaohua Wang

Data Availability Statements

The research outcomes of this study are available from the corresponding author on reasonable request.

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