Construction Quality Control for Ru tt ing Resistance of Asphalt Pavement Using BIM Technology

: During the course of building asphalt pavement, a lack of quality control will lead to the abandonment of the asphalt mixtures. One of the most common problems with asphalt pavement is ru tt ing. Improving the construction’s quality is an important measure to reduce ru tt ing. The purpose is to ensure the high-temperature durability of asphalt mixtures during the construction work-ﬂ ow to reduce the waste of asphalt mixtures, as well as to provide a methodology for the c urrent monitoring of the quality based on the building information modeling (BIM). Ru tt ing resistance was appraised utilizing the static uniaxial creep examination. Oblique photography technology was used to obtain terrain data. The software of Revit 2016 was used to build the spatial model of high-ways and bridges. The results show that the size distribution of particles, the asphalt proportion, and the forming specimen’s temperature are the vital elements in ﬂ uencing the high-temperature behavior. The gradation was identi ﬁ ed as the most important factor. The second was the asphalt binder content. Gradation variation should be given more consideration during paving using asphalt mixtures. Furthermore, the developed BIM platform can also monitor ru tt ing resistance to reduce rework during construction.


Introduction
A lack of construction quality control of asphalt layers will often lead to rework, waste materials, and increased cost [1][2][3][4][5].This is not conducive to the realization of energy saving and emission reduction.On the other hand, rutting is common distressful for asphalt pavements.It does not only affect driving comfort but also threatens driving safety, especially in rain and snow.Researchers found that one of the major factors causing pavement rutting was the construction effects of asphalt mixtures.The leading goal of controlling the construction process is to verify that the quality of asphalt layers satisfies the design requirements.The construction's quality can be well controlled through the detection of construction control indices.The asphalt layer construction's process control is carried out in accordance with the asphalt pavement construction criteria [6,7].However, the pavement construction criteria do not specify which construction quality assurance measures are associated with rutting resistance or the level of impact.According to the construction criteria, the asphalt binder content, raw material properties, rolling temperature, mixture gradation, compaction passes, asphalt layer thickness, compaction level, and evenness are among the construction control indices [6,7].Through analysis, it can be found that the key influencing variables of construction quality and the volumetric parameters of asphalt concrete include the aggregate size distribution, asphalt amount, rolling passes, rolling temperature, and layer thickness.However, there is a lack of research on the asphalt mixtures' performance at high temperatures in construction based on BIM technology control.Leahy [8] used repeated-load triaxial tests and static creep tests to examine the effects of test temperature, deviator stress, asphalt type, asphalt content, aggregate type, and compaction effort on rutting resistance.The factors that influence the formation of ruts are aggregate, binder, mixture, and test field conditions [9].An innovative machine learning approach was applied to estimate the flow value of asphalt concrete [10].The NCHRP report 704 lists several factors that impact the rutting of asphalt pavements [11].Unfortunately, the report does not provide a clear grasp of how these elements influence the genesis of ruts.The sensitivity analysis is not focused on the asphalt layer construction because there are deviations in the values of various factors in the sensitivity analysis in the actual construction process.Moreover, these studies do not provide a comparison of the degree of influence of the aforementioned factors on rutting resistance.It is essential to identify the key indicators of construction control and analyze the impact of various construction control indicators on the asphalt mixtures' performance at high temperatures to reduce raw material waste.
After determining which control indicators need to be monitored, it is also essential to handle the real-time detection of control indicators.Using digital imaging technology [12][13][14][15] or real-time monitoring technology [6,7], the particle size distribution and the asphalt percentage can be prognosticated promptly in the asphalt mixing plant.In addition, GPR can determine the air gap and asphalt surface thickness in actual time [16,17].Furthermore, the conditions of the pavement can also be checked through visual analysis [18,19].
When the construction control indices can be monitored, the next question is how to better monitor the values of construction control indices.Currently, the level of informatization of asphalt mixture layer construction is relatively low in the process of construction [20,21].Construction information is still collected manually and stored in paper files, which severely limits the speed and accuracy of construction quality control.The construction industry has employed Building Information Modeling (BIM) technology to surmount these challenges.To address the challenges of enormous amounts of data analysis, information protection, and cost in the use of the BIM model, Ding et al. [22] designed a cloud-based system for storing BIM concepts.Das et al. [23] proposed an ontological framework leveraging web services to solve the problem of integrating and managing building supply chain data.Lin et al. [24] used machine reading comprehension to solve the problem of quickly finding the required information, and advanced a clever data access technique for cloud-based BIM systems.Sattineni et al. [25] integrated the BIM model and RFID technology for monitoring the status of constructors, equipment, and materials in actual time.Unfortunately, the application of BIM to superintend the construction of asphalt layers has drawn relatively negligible regard.There are many types of BIM software 2016 [26,27].The majority of these types of software are used for road and bridge modeling and design.Only a few BIM platforms provide for real-time monitoring of construction control indices.As a result, a BIM platform for displaying construction data in real-time must be developed.
The aim of this research is to recognize the basic control indicators for asphalt mixtures' performance at high temperatures to reduce their waste during construction and to provide a method based on real-time monitoring of these indicators using the proposed BIM platform.In this study, the gradation, asphalt binder content, temperature control during rolling, segregation of gradation, and segregation of temperature were all taken as factors affecting the asphalt concrete's behavior at elevated temperatures, and it was evaluated using the static uniaxial creep test.More importantly, the BIM system was built for instantaneous tracking of the construction quality with the purpose of reducing their rework.The significance of this study was to identify key indicators of rutting resistance of asphalt mixtures and monitor them using the BIM technology.

Materials and Methods
The key control indicators for rutting resistance during construction were determined and monitored in real time, as presented in Figure 1.

Asphalt
It can be observed from Table 1 that the SBS altered asphalt (I-C) utilized in this research conforms to JTG F40-2004 [6].For this research, AC-13 was prepared using the crushed basalt aggregates of 10-15 mm, 5-10 mm, 3-5 mm, and 0-3 mm.As exhibited in Tables 2 and 3, the attributes of the aggregates and fillers fulfill the technical prerequisites stipulated in [6].

Mixture Design
Figure 2 depicts the grading range of AC-13.The optimum asphalt binder content (OAR) was determined by applying the Marshall testing protocol.The samples were formed at a thermal level of 160 °C.Table 4 displays the outcomes of the mixing design.According to the aforementioned analysis, the size distribution, asphalt binder content, rolling thermal level, number of passes during compaction, and layer depth all play a role in the high-temperature performance.The number of compaction repetitions can be precisely managed with GPS-RTK technology [30].Consequently, the gradation, the asphalt proportion, and the rolling temperature were the primary considered factors evaluated in this study for rutting resistance.Figure 3 shows the permissible variation range of the size distribution in the asphalt mixing plant [6].The maximum amount of variation in asphalt binder content that can be tolerated with ±0.3% [6].The temperature for molding (or rolling) was kept within a design variation range of 15 °C.The appraisals of how these variances influence the high-temperature actions of asphalt mixtures were then evaluated.When assessing the influence of grading fluctuation on asphalt concrete's behavior, it is impractical to accurately attain the intended gradation employing four aggregate sizes.As a result, aggregates of various sizes were sieved into closer size fractions of 0 to 75 µm, 75~150 µm, 150~300 µm, 300~600 µm, 600~1180 µm, 1180~2360 µm, 2360~4750 µm, 4750~9500 µm, 9500~13200 µm, and 13,200~16,000 µm and stored separately.These sieved aggregates were then used to make the asphalt mixture.The asphalt mixtures were created using the sieved aggregates, and the porosity was measured, as shown in Table 5.The problems of segregation of gradation and temperature often occur in asphalt mixtures.Previous studies have shown that these two segregation problems reduce the performance of asphalt mixtures [31][32][33][34][35].Most studies mainly model large areas of isolation.As shown in Figure 4a, the width of the segregation zone approaches or exceeds the rolling width of the roll.Large-area segregation, on the other hand, is uncommon during the regular building of an asphalt layer.In addition, the capability of the asphalt blend in the dissociated area is uncertain when the segregation region's magnitude is smaller than the compactor's flattening width, as exhibited in Figure 4b.Hence, this study chiefly concentrates on examining the effectiveness of limited-area segregation.As demonstrated in Figure 5, four degrees of gradation dissociation were created.It is clear that employing the same asphalt binder percentage as in the control group for asphalt mixtures with gradation segregation is not a good idea.Directly taking cores from the segregation zone and determining the asphalt binder content is the most feasible way.This method, however, will obliterate the asphalt pavement's structure.An alternative approach is to sort the unbound asphalt mixture by passing it through sieves of different sizes, such as 9.5 mm and 4.75 mm sieves.By combining these components, it is possible to produce various asphalt mixtures with different levels of aggregate separation and asphalt content.Unfortunately, the loose modified asphalt mixture tends to clump together, and it is hard to alter the ratio of coarse and fine particles.Furthermore, when it comes to altering the degree of gradation segregation, this method is blind.The effective asphalt film thickness was seen as nearly matching that of the control test batches 1-4 since the graded mixes came from unsegregated asphalt.Employing the statistics in Tables 6 and 7, and Equation ( 1), the effectual layer width of the asphalt coat for the control set can be assessed as 7.59 µm.The functional asphalt ratio can be deduced via reverse calculation when the efficient thickness of the asphalt folio is specified.Equations ( 2) and ( 3) can then be employed to determine the asphalt content.
where DA is the effective thickness of the asphalt film (µm); Pbe is the effective asphalt content (%); γb is the specific gravity of the asphalt (25 °C/25 °C); SA is the specific surface area of the combined aggregate (m 2 /kg); Pba is the proportion of asphalt absorbed into the aggregate (asphalt-aggregate ratio) (%); γse is the effective specific gravity of the combined aggregate; γsb is the bulk specific gravity of the combined aggregate; Pb is the asphalt content (%); and Ps is the ratio of the mass of the aggregates to the mass of the asphalt mixture (%).
According to Reference [36], the computed asphalt binder amount can be adjusted using the following equation: where y represents the revised asphalt binder content (%); and x represents the computed asphalt binder content (%).Table 8 shows the asphalt binder contents of TGs 1~4.This study examined two degrees of temperature separation, and the temperatures for molding were fixed at 145 °C and 130 °C.
As demonstrated in Table 43 shown in NCHRP report 441 [33], the degree of gradation segregation can be evaluated via the surface texture ratio.TG 1 was segregated at a low level, while TG 2 was segregated at a high level.TGs 3 and 4 had a relation with segregation at low and high levels, respectively.Table 5 of the NCHRP report 441 shows the range of temperature variances [33].TGs 5 and 6 were categorized under low-tier and high-tier segregation, in that order.

Estimating the Void Content of Segregated Asphalt Pavement
To measure the void content of segregated zone, the Superpave compaction technique was applied.This study examined the impact of the non-segregation zone on the segregation zone.Figure 6 depicts the mesh mold.Before forming samples, first, it is necessary to measure the weight of both homogeneous and heterogeneous asphalt blends.The Superpave Gyratory Compactor's records showed a correlation between the specimen's height (or air spaces) and the gyrations number.The asphalt mixtures' air voids after paving were about 10% [37] for the road construction project.To reach 10 percent and 3.7 percent air voids, the gyration number needed was 11 and 63, respectively.The height of the specimen for segregated zone with 11 gyrations should be equal to that of the non-segregated zone since both had the same thickness after paving.This is the basis for determining the mass of the segregated specimen.Following that, a preset mass of non-segregated and segregated asphalt pavements was deposited on opposite sides of the barrier.The molds for making specimens were designated to correspond to the partition's position.When the asphalt mixture reaches the predetermined forming temperature, the separator can be removed and placed in the Superpave gyratory compactor for forming.The screen is removed after 63 revolutions.The sample was divided into two parts based on the marking.The cut specimens' air voids were determined following T 0705−2011 [28], and Table 9 shows the results.The research specified a 1:1 ratio between the area of segregation and the area without segregation.By altering the width and position of the divider, different ratios can be achieved.

Method of Preparing and Testing Specimens
The static uniaxial creep tests were engaged to assess rutting resistance.The specimen preparation and testing procedure were conducted according to appendix C of NCHRP report 465 [38].The specimen (150 mm × 165 mm) was molded based on Tables 5  and 9.The flow time can be calculated as follows [39]: where dεi/dt is the creep rate at i sec; εi − Δt is the strain at (i − Δt) sec; εi + Δt is the strain at (i + Δt) sec; Δt is the sampling interval; is the smoothed creep rate at i sec; dεi − 2Δt/dt is the creep rate at (i − 2Δt) sec; dεi − Δt/dt is the creep rate at (i − Δt) sec; dεi + Δt/dt is the creep rate at (i + Δt) sec; and dεi + 2Δt/dt is the creep rate at (i + 2Δt) sec.

BIM System
The BIM system was established by the project team to enable the real-time and intuitive monitoring of the asphalt pavement's construction quality.The platform consists of four components: 3D model of road and bridge, geographical data, tracking data, and system attributes.Among them, 3D models can display the construction information associated with roads and bridges.Topographic data can be used to obtain accurate and clear topographic maps.Construction monitoring indicators and construction control data are obtained through experiments and sensors, respectively.The platform's function is to analyze and display construction information.Figure 7 illustrates the process of constructing the BIM framework.

Pavement Structure Composition
The 3D models were created including subgrade, base course of cement-stabilized macadam, and the surface of asphalt layer in Autodesk Revit 2016 software, and the pavement structure was integrated into the BIM platform.The division of components is based on the paving distance and position of a truck of mixture.The origin of the module is the preliminary paving site of asphalt combination on a lorry.Figure 8 depicts the BIM models for asphalt pavement and subgrade.

Developing BIM Framework
As illustrated in Figure 9, our team created a BIM platform that enabled the tracking of construction data.In the BIM platform, the terrain data can be obtained through oblique photography or existing map data, as shown in Figure 10.The control indicators were measured in the asphalt pavement construction process, and the detection data were uploaded to the data management system of the BIM platform through the 5G/4G network.The components were linked to the observed data.When the component was clicked, the detection data were displayed.In addition, the data from the detection can be displayed and analyzed.For instance, the variation in the asphalt binder content over time can be presented through the BIM platform.The system is accessible to software users from any place where there is a network connection.They can also view and modify models based on their permissions.

Effect of Factors Considered on Rutting Performance
Table 10 presents the orthogonal test results of the rutting performance.The operation of the extremum difference analysis is easy and handy, though it is coarse.The outcomes of the extremum difference analysis are displayed in Table 10.Ij is the summation of flow time values for level 1 in j (j = 1, 2, 3 or 4) column.IIj and IIIj are similar to Ij. Rj is the difference between Ij/3, IIj/3, and IIIj/3's max and min values.
The range reflects the extent to which the influence of the factor level changes on the evaluation indices.The significance of the factors can be assessed based on the ranges provided in Table 10.The order of the factors that influence the outcome, from most to least important, is size distribution, percentage of asphalt, and production temperature.Consequently, the control of size distribution and asphalt binder content in the asphalt mixing plant should be paid more attention to with the purpose of obtaining sufficient anti-rutting performance.
Figure 11 presents the relationship between the factor levels and the flow time.For the defined aggregate size levels, the flow time reduced as the aggregate size level moved from the maximum fluctuation limit through the intended aggregate distribution to the minimum fluctuation limit.The coarser the gradation level, the smaller the particular surface area of the mineral particles.Furthermore, if the asphalt-stone ratio is at a high level, the amount of free asphalt will increase, leading to the decrease of the flow time.For the preset levels of percentage of asphalt, the flow time of the asphalt mixture first goes up and then goes down as the asphalt percentage increases.When the percentage of asphalt changes from 4.7% to 5.0%, the flow time increases accordingly.A higher asphalt binder content can facilitate the compaction effect, enhance the structural asphalt quantity, and improve the asphalt concrete's adhesion.Raising the asphalt binder content from 5.0% to 5.3% results in a reduction in the flow time.If the asphalt binder content exceeds a certain value, the amount of free asphalt increases, resulting in a reduction in the flow time.When the temperature rises between 145 °C and 160 °C during molding, the flow time increases obviously.This is because increasing the molding temperature can lower the asphalt viscosity, contributing to achieving a higher degree of compaction.However, the flow time remains relatively constant with a temperature of 160-175 °C.where QT is the total sum of the deviations' squares.For α = 5%, Fα(2, 2) is 19.Hence, FA was higher than Fα(2, 2), while FB and FC were both smaller than Fα(2, 2).Factor A had a significant impact on the flow time; factors B and C have no significant effect on the evaluation index.

Effect of Segregation on Flow Time
The specimens of the segregated asphalt mixture were molded according to Table 9. Figure 12 displays the outcomes of the static uniaxial creep test for the segregated asphalt mixture.As depicted in Figure 12, when the asphalt concrete's gradation grows coarser as a result of segregation, the flow time of the asphalt concrete at first undergoes a minor increase followed by a decrease.This is due to the fact that as the ratio of coarse aggregates increases, the aggregate's role as a skeletal framework is reinforced.But if the fraction of coarse aggregates exceeds a specific boundary, the asphalt mortar percentage decreases and the bonding capability of the asphalt mixture declines.Conversely, when the size distribution turns finer due to segregation, there is a reduction in the asphalt mixtures' flow time.This is due to the declining fraction of coarse aggregates and rising proportion of asphalt mortar.The skeleton function of the aggregates will be rapidly weakened.In addition, when temperature segregation occurs, the rolling temperature decreases.The asphalt layer's compaction degree is reduced, and the skeleton function of the aggregates is significantly affected.

Comprehensive Comparison of the Extent of Impact of Various Factors on Rutting Resistance
To examine the effect of the fluctuation in individual factors on the anti-rutting of the asphalt mix during the construction phase, it is necessary to incorporate two additional TGs, as depicted in Table 13.With consideration of the unfavorable situation, the gradation level of the lower boundary of variation was selected for the supplementary TG 1 and the asphalt binder content of the upper limit of fluctuation was used for supplementary TG 2. Other conditions were consistent with the control group.According to the results of supplementary TGs 1, 2, and TGs 2, 4, and 6 (as shown in Table 14), it was discovered that numerous components in the construction process had varying degrees of influence on high-temperature performance, ranging from strong to weak, including coarser gradation during mixing, finer gradation from segregation, temperature segregation, and increasing asphalt binder content during the mixing process.When the construction process indices are in the degree of fluctuation in various factors defined in this study, it is important to pay special attention to gradation coarsening in the asphalt mixtures' mixing process and gradation becoming finer owing to segregation.[12,13,40] and asphalt mixing plant online detection technology [6,7] can both determine the mixture gradation and asphalt dosage in the mixing process in real time [6].Currently, the data-logging framework of the asphalt mixing plant can accurately gather data such as the weight of asphalt and aggregate, and accurately calculate the amount of asphalt in the tank.The online examination results for the asphalt binder content for each pot of asphalt mixture in a Chinese road construction project are presented in Figure 13.The online examination demonstrates that the asphalt binder content fluctuates just slightly.For example, between 13:00 and 15:00, there were only two pots of asphalt mixture whose asphalt binder content fluctuated.Table 15 depicts the current gradation of an asphalt mixed pot.A truck can carry several pots of asphalt mix.The gradation and the asphalt proportion of transport can be computed according to the online test outcomes of the asphalt mixing plant.The division of the components of asphalt layers is carried out according to the paving distance and position of a truck of the mixture.Thus, the construction information will correspond to the components.

Rolling Temperature
The initial rolling temperature is measured using an infrared temperature sensor, and the temperature value is sent to the data-processing center, as shown in Figure 14.The primary task is to correspond the collected temperature values to the components of the pavement.In the course of paving, the starting and ending pile numbers of the asphalt mixture for transport have been determined, and the location information of the initial rolling temperature can be used to determine the corresponding relationship between the temperature detection values and the components.For the section between K11 + 986.2 and K12 + 44.1 of the road construction project in China, Table 16 provides the temperature readings obtained via infrared thermography.construction indicators exceed the warning range, construction should be suspended and remedial measures should be taken.This can reduce the rework and the waste of asphalt mixtures.

Conclusions
In this study, the major construction management indices for rutting resistance were determined to reduce the rework of asphalt layers, and a method for real-time monitoring of these indices using BIM technology was proposed.Rutting resistance was determined by measuring the flow time.Furthermore, the influence of the non-segregation zone on the segregation zone was considered for the asphalt mixtures' performance at high temperatures.This research's BIM platform was the basis for the real-time tracking of the construction control indices.
(1) With the factor levels set, the order of impact that the three factors exert on the asphalt mixtures' performance at high temperatures is size distribution, asphalt binder content, and temperature for molding.Consequently, it is crucial to manage the variation in gradation for the asphalt mixing plant.(2) A slight increase in coarseness in gradation due to segregation can positively impact the asphalt mixtures' performance at high temperatures.However, when the gradation variation surpasses a certain degree, the flow time decreases rapidly.In contrast, the asphalt mixtures' performance at high temperatures is adversely affected when the gradation becomes finer due to segregation.(3) The asphalt mixtures' performance at high temperatures declines with an increasing degree of temperature segregation.In addition, there's a decrease of about 17.3~30.4% in flow time due to the temperature segregation.(4) Rutting resistance is notably affected by the fluctuation in gradation, which includes the process of gradation coarsening during mixing and the occurrence of finer gradation due to segregation.(5) The BIM system was put forward to follow the instantaneous detection information from the asphalt layer's construction.This platform allows construction workers to rapidly appraise the quality of the construction, thereby avoiding the asphalt mixture waste.

Figure 2 .
Figure 2. Designing construction control indices with variability.

Figure 4 .
Figure 4. Illustration of the segregated section: (a) segregation with large area; (b) segregation with small area.

Figure 5 .
Figure 5. Four-level scheme of segregation for size-grade distribution.

Figure 7 .
Figure 7. Process of constructing the BIM framework.

Figure 10 .
Figure 10.Terrain data derived from oblique photography.

Figure 13 .
Figure 13.Online detection of the asphalt binder percentage of asphalt mixing plant.

Figure 15 .
Figure 15.Construction information associated with a component.

Table 2 .
Characteristics of the aggregates.

Table 4 .
Marshall test results.

Table 5 .
Results of Marshall compaction tests.

Table 6 .
Results from testing the density of aggregates with different sizes.

Table 7 .
Data for determining the effective coating thickness of the control group.

Table 10 .
Results of orthogonal test for asphalt mixtures' performance at high temperatures.

Table 11 .
Variance analysis in calculation process.

Table 12 .
Results of variance analysis.

Table 13 .
Mixture percentages of supplementary TGs.

Table 14 .
Comparison of impact degree of multiple factors on high-temperature performance.

Table 15 .
Online detection of the asphalt binder content.

10-15 mm 5-10 mm 3-5 mm 0-3 mm Limestone Filler Asphalt
Author Contributions: Conceptualization, Y.Z. and J.R.; methodology, Y.Z. and K.Z.; software, Y.Z.; validation, Y.L.; formal analysis, K.W.; investigation, Y.Z.; resources, Y.Z. and K.Z.; data curation, Y.Z.; writing-original draft preparation, Y.Z.; writing-review and editing, Y.Z.; visualization, Y.Z.; funding acquisition, Y.Z. and K.Z.All authors have read and agreed to the published version of the manuscript.This study was supported by Shandong Provincial Natural Science Foundation (ZR2020QE274), Key Research and Development Program of Shandong Province (2020RKB01602), Science and Technology Plan of Shandong Transportation Department (2022B102, 2023B92-01), Yangzhou Government-Yangzhou University Cooperative Platform Project for Science and Technology Innovation (Grant No.YZ2020262), Open Project of Shandong Key Laboratory of Highway Technology and Safety Assessment (SH202103), Key project of Natural Science Research of Anhui Provincial Department of Education (2023AH052853), Key Project of Excellent Youth Talent Program in Anhui Universities (gxyqZD2022101), and Quality Engineering Project of Colleges and Universities in Anhui Province (2021jyxm1116, 2022kcsz218). Funding: