Search

A recurrent challenge on cycle paths are edge cracks, which affect the traffic safety and accessibility of cyclists and produce high maintenance costs. Being both structurally thinner and narrower structures than roads, the cycle paths are extra prone to this problem. A few passages of heavy vehicles in unfavourable conditions might be enough to break the edge. The load-bearing capacity of eight municipal cycle paths in Linköping, Sweden, were assessed by falling weight deflectometer (FWD) and light falling weight deflectometer (LWD) measurements during a year-long cycle. A set of alternative Deflection Bowl Parameters (DBPs), better adapted to the structural design of cycle paths, were suggested and evaluated. The results of the FWD measurements showed that these suggested DBPs are a promising approach to evaluate the load-bearing capacity of cycle paths. From the results of the LWD measurements, it was found that the load-bearing capacity varies considerably with lateral position. The conclusion is that it might be more fruitful to measure the load-bearing capacity by LWD close to the edge, rather than the traditional approach of FWD measurements along the centre line of the cycle path. [ABSTRACT FROM AUTHOR]

This study focuses on the seasonal variations observed in five Falling Weight Deflectometer (FWD) tests conducted on a well-instrumented composite pavement. The main objective is to investigate the underlying mechanisms driving these seasonal variations and propose a method to facilitate the comparison of the different FWD tests. The stiffnesses of concrete, asphalt, and cement-stabilised layers are characterised individually. The stiffness of the subgrade is back-calculated using multi-layered simulations. These simulations also enable computation of deflections for different asphalt temperatures. The results allow for developing a method which converts measured deflections into corrected deflections referring to an asphalt reference temperature. Remaining seasonal variations of the corrected deflections refer to the subgrade. Corresponding k-values of the AREA4 method correlate well with seasonal variations of the stiffness of the subgrade. Finally, an alternative temperature-correction approach, requiring measured deflections only, is developed. Corrected deflections allow for quantifying seasonal stiffness variations of the subgrade. [ABSTRACT FROM AUTHOR]

Non-destructive testing (NDT) systems are essential tools and are widely used for assessing the condition and structural integrity of pavement structures without causing any damage. They are cost-effective, provide comprehensive data, and are time efficient. The bearing capacity and structural condition of a flexible pavement depends on several interrelated factors, with asphalt layers stiffness being dominant. Since asphalt mix is a viscoelastic material, its performance can be fully captured by the dynamic modulus master curve. However, in terms of evaluating an in-service pavement, although a dynamic load is applied and the time history of deflections is recorded during testing of FWD, only the peak deflection is considered in the analysis. Therefore, the modulus of stiffness estimated by backcalculation is the modulus of elasticity. While several methods have been introduced for the determination of the field dynamic modulus master curve, the MEPDG approach provides significant advantages in terms of transparency and robustness. This study focuses on evaluating the methodology's accuracy through an experimental study. The data analysis and validation process showed that routine measurements with the FWD and GPR, within the framework of a pavement monitoring system, can provide valuable input parameters for the evaluation of in-service pavements. [ABSTRACT FROM AUTHOR]

The successful management of road pavement maintenance requires the existence of suitable monitoring procedures for assessing pavement condition. A powerful tool for this is the use of non-destructive testing technologies. Non-destructive testing (NDT) aims to support the monitoring of pavement condition, as it enables constant and rapid collection of in situ data. Analyzing NDT data can result in the development of useful indexes that can be related to trigger values (criteria) to define pavement condition. This information can be used to assess the "health" of the pavement to decide whether intervention is required. However, to effectively support the implementation of pavement management measures, it is sometimes necessary to implement a pavement monitoring and assessment framework that can be adapted by road authorities on a case-by-case basis. To this end, this study addresses the development of a pavement monitoring and assessment procedure by integrating different NDT technologies to collect and evaluate data. The procedure, referred to as Integrated Testing and Evaluation (ITE), is proposed as an algorithm to find optimal strategies for prioritizing potential pavement interventions, considering the budget constraints for the required investigations. [ABSTRACT FROM AUTHOR]

Non-destructive testing (NDT) systems are essential tools and are widely used for assessing the condition and structural integrity of pavement structures without causing any damage. They are cost-effective, provide comprehensive data, and are time efficient. The bearing capacity and structural condition of a flexible pavement depends on several interrelated factors, with asphalt layers stiffness being dominant. Since asphalt mix is a viscoelastic material, its performance can be fully captured by the dynamic modulus master curve. However, in terms of evaluating an in-service pavement, although a dynamic load is applied and the time history of deflections is recorded during testing of FWD, only the peak deflection is considered in the analysis. Therefore, the modulus of stiffness estimated by backcalculation is the modulus of elasticity. While several methods have been introduced for the determination of the field dynamic modulus master curve, the MEPDG approach provides significant advantages in terms of transparency and robustness. This study focuses on evaluating the methodology’s accuracy through an experimental study. The data analysis and validation process showed that routine measurements with the FWD and GPR, within the framework of a pavement monitoring system, can provide valuable input parameters for the evaluation of in-service pavements.

The successful management of road pavement maintenance requires the existence of suitable monitoring procedures for assessing pavement condition. A powerful tool for this is the use of non-destructive testing technologies. Non-destructive testing (NDT) aims to support the monitoring of pavement condition, as it enables constant and rapid collection of in situ data. Analyzing NDT data can result in the development of useful indexes that can be related to trigger values (criteria) to define pavement condition. This information can be used to assess the “health” of the pavement to decide whether intervention is required. However, to effectively support the implementation of pavement management measures, it is sometimes necessary to implement a pavement monitoring and assessment framework that can be adapted by road authorities on a case-by-case basis. To this end, this study addresses the development of a pavement monitoring and assessment procedure by integrating different NDT technologies to collect and evaluate data. The procedure, referred to as Integrated Testing and Evaluation (ITE), is proposed as an algorithm to find optimal strategies for prioritizing potential pavement interventions, considering the budget constraints for the required investigations.

Abstract This paper focuses on the methodology for evaluating the degree of total curling in concrete pavement using machine learning. Deflection induced by falling weight deflectometer (FWD) testing is known as a direct correlation to total curling including built-in and daily curling. However, deflection measurement in the in-service road is also affected by others, such as environmental conditions, pavement geometry, subgrade stiffness, and mixture design. Thus, it is challenging to determine the level of curling from FWD data due to the complexity of influencing parameters. To navigate this complexity, prominent machine learning models are exploited to identify a non-linear relationship between curling and FWD deflections. A finite-element simulation of FWD is conducted to generate a vast data set, and a robust regression model is trained to estimate the total effective temperature difference (TETD) to quantify the effects of curling. Since input parameters for testing pavements can be measurable in the field, curling from TETD can be readily obtained using the proposed methodology. Comparative simulations highlight that the proposed models, with an MAE less than 0.5 °C significantly outperform the multiple regression performance, which registers an MAE of 3.45 °C in TETD, particularly in offering cost-effective and noise-tolerant prediction.

This paper focuses on the methodology for evaluating the degree of total curling in concrete pavement using machine learning. Deflection induced by falling weight deflectometer (FWD) testing is known as a direct correlation to total curling including built-in and daily curling. However, deflection measurement in the in-service road is also affected by others, such as environmental conditions, pavement geometry, subgrade stiffness, and mixture design. Thus, it is challenging to determine the level of curling from FWD data due to the complexity of influencing parameters. To navigate this complexity, prominent machine learning models are exploited to identify a non-linear relationship between curling and FWD deflections. A finite-element simulation of FWD is conducted to generate a vast data set, and a robust regression model is trained to estimate the total effective temperature difference (TETD) to quantify the effects of curling. Since input parameters for testing pavements can be measurable in the field, curling from TETD can be readily obtained using the proposed methodology. Comparative simulations highlight that the proposed models, with an MAE less than 0.5 °C significantly outperform the multiple regression performance, which registers an MAE of 3.45 °C in TETD, particularly in offering cost-effective and noise-tolerant prediction. [ABSTRACT FROM AUTHOR]

In the case analysed, a glass fibre mesh was applied under the asphalt layer during a rehabilitation treatment. Because only one lane was reinforced, the test section can be used to observe the influence of glass fibre mesh on the relationship between the selected deflection basin parameters (RoC, BLI, MLI, and LLI) and back-calculated pavement layer moduli. The FWD measures were used to determine the bowl of deflection indicators and to back-calculate the layer’s moduli. The values of DBP-s allowed confirmation of the technical condition of pavement construction. The first measures were carried out in 2019 and repeated in 2021; the results were then compared and analysed. Influence was observed on the relationship between the deflection basin and moduli, especially for the base course and subgrade. The reinforced lane showed a better coefficient of determination between DBPs and moduli in 2019, but in 2021 relationships were observed only for LLI and subgrade moduli. The unreinforced lane, however, showed the mentioned relationships in both 2019 and 2021. Because of a relatively small number of measurement points, the presented analyses and observations should be considered as preliminary. Presented results and relationships are another step into developing an alternative approach to determining the initial pavement moduli i.e. to use as a seed moduli.

A recurrent challenge on cycle paths are edge cracks, which affect the traffic safety and accessibility of cyclists and produce high maintenance costs. Being both structurally thinner and narrower structures than roads, the cycle paths are extra prone to this problem. A few passages of heavy vehicles in unfavourable conditions might be enough to break the edge. The load-bearing capacity of eight municipal cycle paths in Linköping, Sweden, were assessed by falling weight deflectometer (FWD) and light falling weight deflectometer (LWD) measurements during a year-long cycle. A set of alternative Deflection Bowl Parameters (DBPs), better adapted to the structural design of cycle paths, were suggested and evaluated. The results of the FWD measurements showed that these suggested DBPs are a promising approach to evaluate the load-bearing capacity of cycle paths. From the results of the LWD measurements, it was found that the load-bearing capacity varies considerably with lateral position. The conclusion is that it might be more fruitful to measure the load-bearing capacity by LWD close to the edge, rather than the traditional approach of FWD measurements along the centre line of the cycle path.

Copyright of Archives of Civil Engineering (Polish Academy of Sciences) is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the increased use of heavy commercial vehicles with higher axle weights has required the development of innovative technologies to improve the mechanical properties of asphalt concrete conglomerates, such as fatigue resistance and rutting. This study offers a comprehensive comparative analysis of different types of asphalt concrete tested in four trial sections (S1, S2, S3, S4) of the SP3 Ardeatina rural road in Rome, under actual traffic and operational conditions. More precisely, the pavement technologies applied include modified asphalt concrete with graphene and recycled hard plastics for S1, asphalt concrete modified with styrene–butadiene–styrene (SBS) for S2, asphalt concrete with a standard polymeric compound for S3, and traditional asphalt concrete for S4. The evaluation approach involved visual inspections in order to calculate the pavement condition index (PCI) and falling weight deflectometer (FWD) tests. In addition, back-calculation analyses were performed using ELMOD software to assess the mechanical properties. The laboratory tests revealed superior properties of M1 in terms of its resistance to permanent deformations (+13%, +15%, and +19.5% compared to M2, M3, and M4, respectively) and stiffness (10,758 MPa for M1 vs. 9259 MPa, 7643 MPa, and 7289 MPa for M2, M3, and M4, respectively). These findings were further corroborated by the PCI values (PCIS1 = 65; PCIS2 = 17; PCIS3 = 28; PCIS4 = 29) as well as the FWD test results after 5 years of investigation, which suggests greater durability and resistance than the other sections. [ABSTRACT FROM AUTHOR]

Condition assessment and maintenance of vast road networks is a challenge both technically and financially in many low and middle-income countries (LMICs). It often requires rapid data collection techniques, quick analysis of the data, accurate defect identification, and appropriate allocation of scarce funds. The Falling Weight Deflectometer (FWD) equipment can be used for rapid non-destructive techniques of assessing the condition of road pavement layers. Many road agencies in LMICs are acquiring FWDs and Pavement Management Systems (PMS) for data collection and maintenance planning. The analysis of FWD data requires rigorous back-calculation techniques that cannot be easily integrated into PMS. Surface deflection bowl parameters (DBP) have since been used for classification of pavement conditions. However, DBP do not yield values of layer elastic moduli, that are increasingly being used in rehabilitation design. Moreover, the DBP that are currently in use are applicable to roads with at least 50 mm asphalt concrete surfacing and have not been checked for validity on roads incorporating thin bituminous seals such as chip seal, and cape seal. Thus, a system that rapidly estimates layer elastic moduli from DBP and that can be easily integrated into PMS is required now and in the near future, for LMICs. Defective sections or pavement layers identified through this approach can then undergo more rigorous analysis using FWD specialist back-calculation software. This study developed equations that reliably estimate the layer moduli from DBP of pavements surfaced with thin bituminous seals. This was done through conducting FWD tests on selected road sections, conducting back-calculation using specialist software, and testing which DBP best correlates with the back-calculated elastic moduli. These equations are used to rapidly identify pavement layers and sections that are deteriorating season by season, and hence, target and plan appropriate maintenance interventions.

Condition assessment and maintenance of vast road networks is a challenge both technically and financially in many low and middle-income countries (LMICs). It often requires rapid data collection techniques, quick analysis of the data, accurate defect identification, and appropriate allocation of scarce funds. The Falling Weight Deflectometer (FWD) equipment can be used for rapid non-destructive techniques of assessing the condition of road pavement layers. Many road agencies in LMICs are acquiring FWDs and Pavement Management Systems (PMS) for data collection and maintenance planning. The analysis of FWD data requires rigorous backcalculation techniques that cannot be easily integrated into PMS. Surface deflection bowl parameters (DBP) have since been used for classification of pavement conditions. However, DBP do not yield values of layer elastic moduli, that are increasingly being used in rehabilitation design. Moreover, the DBP that are currently in use are applicable to roads with at least 50 mm asphalt concrete surfacing and have not been checked for validity on roads incorporating thin bituminous seals such as chip seal, and cape seal. Thus, a system that rapidly estimates layer elastic moduli from DBP and that can be easily integrated into PMS is required now and in the near future, for LMICs. Defective sections or pavement layers identified through this approach can then undergo more rigorous analysis using FWD specialist back-calculation software. This study developed equations that reliably estimate the layer moduli from DBP of pavements surfaced with thin bituminous seals. This was done through conducting FWD tests on selected road sections, conducting back-calculation using specialist software, and testing which DBP best correlates with the back-calculated elastic moduli. These equations are used to rapidly identify pavement layers and sections that are deteriorating season by season, and hence, target and plan appropriate maintenance interventions. [ABSTRACT FROM AUTHOR]

The assessment of asymmetric slab behaviour is out of reach in standard Falling Weight Deflectometer (FWD) tests, because deflections are measured along the driving direction only. Herein, a new T-shaped arrangement of the geophones is proposed. It allows for rapid quantification of asymmetric slab behaviour in central FWD testing of concrete slabs. One geophone is positioned at the centre of impact (= centre of the slab), six along the driving direction, one right and one left of the centre. The 'Lateral Asymmetry Index (LASIX)' is introduced as a corresponding dimensionless deflection basin parameter. Its value increases with increasing asymmetric behaviour of the slab. The main research challenge tackled herein is to optimise the radial distance of the lateral geophones from the centre of the slab, such as to maximise the expressiveness of LASIX for the quantification of asymmetric slab behaviour. In this context, FWD tests with measurement of deflections in eight different directions are carried out, and the 'effective asymmetry index (${\cal A}_{28}$ A 28 )' is introduced as another new dimensionless deflection basin parameter. It summarises the asymmetric behaviour based on deflection differences quantified for all 28 pairs of directions which can be combined out of the eight available measurement directions. The optimal radial distance of the lateral geophones from the centre of the slab is found as 1.20 m. Corresponding values of LASIX larger than $8\percnt$ 8 % refer to coefficients of directional variation of the AREA7 parameter larger than 5%. This indicates directional degradation of the pavement structure resulting from eccentric traffic loads. T-shaped FWD testing requires in situ efforts equivalent to those of standard testing, while allowing for a rapid and reliable quantification of asymmetric behaviour. It allows for the assessment of whether the standard evaluation of uniform moduli of subgrade reaction is realistic or questionable. [ABSTRACT FROM AUTHOR]

Falling Weight Deflectometry (FWD) tests are performed around the centres of two rectangular concrete plates, with geophones measuring vertical deflections in eight directions. Experimental results allow for quantifying asymmetries regarding the structural behaviour. Significant asymmetries are found for a 22-year-old plate scheduled for replacement. A new plate, tested a few weeks after production, is found to behave in a virtually double-symmetric fashion. Structural analysis of the new plate is based on Kirchhoff–Love plate theory, using free-edge boundary conditions. The support of the plate is provided by a Winkler foundation. Performing a static analysis, the uniform modulus of subgrade reaction is optimised to reproduce the measured deflections. The result is not convincing. The model is extended towards consideration of a second optimisation variable: a uniform auxiliary surface load. This allows for reproducing the measured deflections. The auxiliary load is superimposed with the pressure resulting from the Winkler foundation. This yields a realistic distribution of subgrade pressure. Dividing it by the deflections results in the distribution of the effective modulus of subgrade reaction. Finally, the analysis is extended towards the consideration of inertia forces. They increase the effective moduli of subgrade reaction determined by means of static analysis by less than 3.5%. [ABSTRACT FROM AUTHOR]

Overlay design must consider factors such as traffic load, soil characteristics, existing pavement condition, and planned changes to road design. This overlay calculation procedure is usually performed using technically recognized pavement design methods, such as the AASHTO 1993 (Guide for Design of Pavement Structure) calculation method. The research conducted is a method to determine the design algorithm of thick, layer added using asphalt coating on concrete roads based on AASHTO 1993 standards. The data used in this study were pavement design data and Falling Weight Deflectometer (FWD) deflection data. The cumulative value of traffic load used is 35,000,000 million and then calculated using lane distribution factors and directions, the resulting w18 value is 8,750,000 million, then the result of calculating the thickness of the plate to serve future traffic (Df) is 11.64 inches or 29.57 cm and the effective plate thickness value (Deff) is 9.45 inches or 24.01 cm, Factor A of converting concrete thickness into asphalt thickness is 1.93 inches or 4.91 cm, then the result of layer added thickness (Dol) is 4.24 inches or 10.77 cm. This design is influenced by Falling Weight Deflectometer (FWD) deflection data so that the calculation of the added layer thickness is analyzed at each station point (STA). [ABSTRACT FROM AUTHOR]

Rehabilitation treatments applied to a local road prone to terrain subsidence from mining excavation should be designed considering cost-efficient and effective reinforcement solutions. In the analysed case, a glass-fibre mesh was applied under asphalt concrete layers in 2008, in one lane while another was left without the reinforcement. The main objective of this paper was to investigate the effectiveness of reinforcement by analysing the amount of produced on the pavement and the influence on pavement deflection. It was found that the reinforcement retracted the number of cracks, however, did not affect the bearing capacity. The influence of the applied geosynthetic was manifested in the values of the radius of curvature. The overall technical state of the road requires immediate treatment and the applied reinforcement proved obsolete because in this particular case of road located in the mining active terrain the glass fiber mesh did not prolong the life of the pavement.

Artificial walking survey, ground penetrating radar (GPR) and falling weight deflectometer (FWD) were used to test the actual condition of the highway pavement in reconstruction and expansion project for better maintenance decision-making. Therefore, a decision-making system with the application of four evaluation indexes including deflection value (DV), pavement surface condition within 20 m(PCI20), maintenance effect (ME) and internal crack rate (ICR) was constructed. Through the pavement empirical-mechanical calculation and the Delphi method analysis, the corresponding threshold for the DV, PCI20 and ICR were 27 (0.01 mm), 80, and 20 m/100 m2 respectively. Then, the decision-making system was applied for the 5.5 km section with the detection and evaluation results, and the advised maintenance plans of different lanes were determined. Lastly, the effect of the decision-making system was analyzed. Results show that the decision-making system can scientifically decide the treatment plans and save the maintenance cost by about 30.1 %. The deflection near the grouting holes significantly decreases resulting from the high-density cement slurry distribution. The milling and repaving have a high structural reinforcement ability of reducing deflection up to more than 66 %, which is positively related to the milling depth.

Copyright of Roads & Bridges / Drogi i Mosty is the property of Road & Bridge Research Institute and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This research aimed to investigate the attenuation mode of the layer modulus of asphalt pavement in accelerated pavement testing (APT). A full-scale experimental section was constructed and tested using the APT facility. Two non-destructive testing (NDT) methods, named falling weight deflectometer (FWD) technique and portable seismic property analyzer (PSPA) test, were used to obtain the layer moduli of asphalt pavement during the APT test. The variation patterns of layer moduli obtained by FWD and PSPA tests were calculated and compared after the temperature was corrected to 20 ℃. It was found that the variation pattern of surface layer modulus based on field FWD measurements was consistent with the one measured from PSPA tests. That is the modulus of the surface layer increases with the APT load repetitions firstly and then decreases with the rise of the repetitions. The modulus values of the surface layer measured from PSPA tests are obviously larger than those backcalculated based on deflection basins. The ratio of the measured surface layer modulus based on the PSPA test to the backcalculated one based on the FWD test ranges between 2.06 and 2.71. The backcalculated base layer modulus always declines with the increasing loading repetitions. The attenuation patterns of the surface layer modulus and the base layer modulus in the damage stage are described as Ea=421100*N-0.6119 and Eb=128000*N-0.1096, respectively.

This paper highlights the application of non-destructive tests (NDT) to evaluate the pavement for maintenance in a road network. The falling weight deflectometer (FWD) and the network survey vehicle (NSV) test data which is rational in terms of technical, financial, and environmental aspects have been used. The data using NDT devices were collected from a network of roads from Odisha state, India, and analyzed to assess the structural adequacy of the pavements. Further, using the FWD deflection data, the resilient moduli (MR) of the pavements were back-calculated using a cuckoo search (BACKCSA) model developed as a part of this research work. The back-calculated layer moduli (MR) was used as an input for developing the pavement condition index (PCI) prediction model. In addition, the other pavement distresses viz., international roughness index (IRI), rut depth, cracking, and raveling was also collected using the NSV. The data collected for three cycles with a minimum difference of one year between each cycle was used for the development of perdition models. The NSV data was used for developing the multilinear regression (MLR) prediction models for building a comprehensive pavement management system. This paper highlights the novel approach in arriving at the MR, and incorporating the same in MLR models for predicting the maintenance strategy for a road network. [ABSTRACT FROM AUTHOR]

Highway networks are the most widely used transportation network in Turkey. It is very important to determine the maintenance and repair needs correctly and to apply appropriate methods at the right time in order to manage the large resources used in road construction and to reduce the expenditures to the optimum level. The current structural and functional condition of the pavement should be determined in the maintenance - repair planning. The existing structural and functional condition can be determined by methods such as laboratory studies and research pit, or it can be determined using non-destructive testing methods. The structural condition of the road pavement can be determined non-destructively with Falling Weight Deflectometers (FWD). In FWD measurements on flexible pavements, the measurement results of Hot Mixture Asphalt (HMA) layers vary by temperature. In this study, the effect of asphalt temperature on deflection measurements of flexible pavements was investigated. [ABSTRACT FROM AUTHOR]

The falling weight deflectometer (FWD) detection system benefits from its outstanding characteristics of no damage, fast speed, and high precision. The warping deformation of cement concrete pavement occurs due to the temperature difference along the depth of the slab, which makes FWD detect different results under different temperature fields. In this study, we systematically carried out the cement pavement's temperature field and deflection test. The experimental data were analyzed to obtain the temperature variation law of the top and bottom of the pavement slab every day. By establishing a three-dimensional finite element model of cement pavement with a multi-layer elastic foundation type, the influence of the temperature difference at the bottom of the slab on the deflection of the center point of the slab corner load under different working conditions, different seasons, different loads and whether there is polymer filling in the void area was studied. We summarize the correlation between the temperature difference and the influence coefficient and propose the cement pavement void identification and polymer grouting effect evaluation method considering the temperature effect. [ABSTRACT FROM AUTHOR]

Copyright of Archives of Civil Engineering (Polish Academy of Sciences) is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, the increased use of heavy commercial vehicles with higher axle weights has required the development of innovative technologies to improve the mechanical properties of asphalt concrete conglomerates, such as fatigue resistance and rutting. This study offers a comprehensive comparative analysis of different types of asphalt concrete tested in four trial sections (S1, S2, S3, S4) of the SP3 Ardeatina rural road in Rome, under actual traffic and operational conditions. More precisely, the pavement technologies applied include modified asphalt concrete with graphene and recycled hard plastics for S1, asphalt concrete modified with styrene–butadiene–styrene (SBS) for S2, asphalt concrete with a standard polymeric compound for S3, and traditional asphalt concrete for S4. The evaluation approach involved visual inspections in order to calculate the pavement condition index (PCI) and falling weight deflectometer (FWD) tests. In addition, back-calculation analyses were performed using ELMOD software to assess the mechanical properties. The laboratory tests revealed superior properties of M1 in terms of its resistance to permanent deformations (+13%, +15%, and +19.5% compared to M2, M3, and M4, respectively) and stiffness (10,758 MPa for M1 vs. 9259 MPa, 7643 MPa, and 7289 MPa for M2, M3, and M4, respectively). These findings were further corroborated by the PCI values (PCIS1 = 65; PCIS2 = 17; PCIS3 = 28; PCIS4 = 29) as well as the FWD test results after 5 years of investigation, which suggests greater durability and resistance than the other sections.

This paper highlights the subgrade resilient modulus (MR), which is recognized as an important parameter to characterize the stiffness of the subgrade soil for designing flexible pavement. In this study, 18 thin-walled Shelby tube samples of fine-grained subgrade soils were collected from two sites in South Carolina (Laurens/SC-72 and Pickens/SC-93) and tested in the laboratory using AASHTO T307-99 to obtain the MR. In addition, falling weight deflectometer (FWD) tests were performed on the same pavement sections to obtain the back-calculated MR(FWD) per the AASHTOWare 2017 back-calculation tool. A subgrade MR catalog was established and used to select hierarchical Input Level 2 for Pavement Mechanistic-Empirical design (PMED) analysis (v 2.6.1). The PMED analysis was run for 20 years. The Mechanistic-Empirical Pavement Design Guide (MEPDG) and global calibration values were used to predict asphalt concrete (AC) pavement distresses (e.g., rutting, bottom-up fatigue, top-down fatigue, and transverse cracking) and International Roughness Index (IRI) for each pavement section. The predicted values were compared to the field-measured values to determine bias and the standard error of the estimate to validate each distress prediction model for local calibration. [ABSTRACT FROM AUTHOR]

The traditional practice for pavement structural capacity evaluation is mostly dependent on the falling weight deflectometer (FWD) measurements. However, this practice has several challenges due to its stationary nature. Recently, a Rolling Weight Deflectometer (RWD), capable of measuring the pavement deflections at regular traffic speeds, has been introduced into the market. This research aims to develop a finite element (FE) model simulating pavement structural response under the moving RWD loads. This model could be further utilised for accurately estimating pavement layers mechanical characteristics. The model was successfully validated utilising the RAPTOR (a commercially available RWD) data collected on the National Center for Asphalt Technology (NCAT) test track. A good correlation between the simulated and the measured values was found – yielding an average root mean square percentage error (RMSPE) of approximately 2.40% between the RAPTOR and the FE deflections. [ABSTRACT FROM AUTHOR]

In developing countries, it is necessary to have appropriate transport infrastructure and industrial facilities that support the fluctuating loads from increased use over time. The in situ concrete block pavements (ISCBP) arise as a cost-effective alternative to the traditional solutions. Few studies that analyse the structural behaviour of ISCBP mention that it works like a flexible pavement. However, these studies are based on experience and results of surface deflections. To analyse the behaviour of ISCBP, two test sections were constructed, in which the vertical stresses, generated by mobile and impact loads (HWD) with different load levels, were measured in the granular base. The results were compared using a layered elastic analysis programme (MnLayer). Under the conditions of this study, the comparison between the measured vertical stresses and those estimated by the programme indicated that the ISCBP presented a linear elastic behaviour. Similar to a flexible pavement, ISCBP reached coefficients of determination (R2) in the order of 0.99 and biases that ranged from 11% to 48% when applying impact loads. Nevertheless, the modulus of the block layer demonstrated that it is dependent on thickness. [ABSTRACT FROM AUTHOR]

The deep forest is a powerful deep-learning algorithm that has been applied in certain fields. In this study, a deep forest (DF) model was developed to predict the central deflection measured by a falling weight deflectometer (FWD). In total, 11,075 samples containing information related to pavement structure, traffic conditions, and weather conditions were extracted from the LTPP dataset. The performance of the DF model with custom backend settings was compared with that of models random forest (RF), multilayer perceptron (MLP), and DF built on the sklearn backend. All four deep-learning algorithms could identify the complex relationship between central deflection and relevant feature variables with high accuracy and stability. The learning and generalization abilities of DF was stronger than those of MLP and RF. The predictive performance and computation time of DF (custom) were better than those of DF (sklearn), indicating that the custom model was superior to the highly encapsulated model with sklearn as the backend. Feature importance analysis indicated that the drop load of FWD was the key factor influencing deflection. In addition, structural number, annual precipitation, and annual kilo equivalent standard axle load (kESAL) are very important features related with deflection. The feature importance of rehabilitation improvement thickness was less than the drop load, climatic factors, kESAL, structural number, and layer thickness. [ABSTRACT FROM AUTHOR]

Remaining life is an important indicator of pavement residual effective service time and is directly related to maintenance decision-making with limited funds. This paper proposes a fast and non-destructive model to predict the remaining life of rigid PCC (Portland cement concrete) pavement, with or without asphalt overlay. Firstly, a model was constructed according to the current Chinese design specifications for concrete pavement integrating an inverse design concept. Secondly, the prediction model was applied to three typical pavement sections with 1430, 1250 and 1000 slabs, respectively. Ground penetrating radar (GPR) was utilized to determine the geometric parameters in the predictive model and the physical state of the pavement. A falling weight detector (FWD) was utilized for determination of the mechanical parameters. A more reasonable equivalent elastic modulus of foundation was back-calculated instead of using the limited model in the design specification. Thirdly, the remaining life was predicted based on the current mechanical and geometric parameters. The distributions of the remaining life of the three pavement sections was statistically analyzed. Finally, a decision-making system to inform maintenance strategy was proposed based on the remaining life and the technical condition of each slab. The results showed that the relationship between the remaining life and the mechanical parameters, geometric parameters and the physical state of the pavement was highly consistent with engineering experience. The success rate of the prediction model was as high as 96%. The proposed fast and non-destructive prediction model showed good engineering applicability and feasibility. The decision-making system was shown to be feasible in terms of economic benefits. [ABSTRACT FROM AUTHOR]

The use of non-destructive testing (NDT) equipment, such as the falling weight deflectometer (FWD), provides important estimates of road health and helps to optimize road management regimes. However, periodic road testing and post-processing of the collected data are cumbersome and require much expertise, a considerable amount of time, money, and other resources. This study attempts to develop a reliable prediction method for estimating the deflection basin area of different asphalt pavements using road temperature, load time, and load pressure as main characteristics. The data are obtained from 19 kinds of asphalt pavements on a 2.038-km-long full-scale field accelerated pavement testing track named as RIOHTrack (Research Institute of Highway Track) in Tongzhou, Beijing. In addition, a chaotic particle swarm algorithm (CPSO) and a segmented regression strategy are proposed in this paper to optimize the XGBoost model. The experiment results of the proposed method are compared with those of classical machine learning algorithms and achieve an average of mean square error and mean absolute error respectively by 5.80 and 1.59. The experiments demonstrate the superiority of the XGBoost algorithm over classical machine learning methods in dealing with nonlinear problems in road engineering. Significantly, the method can reduce the frequency of deflection tests without affecting its estimation accuracy, which is a promising alternative way to facilitate the rapid assessment of pavement conditions. [ABSTRACT FROM AUTHOR]

The use of recycled plastic in asphalt pavements represents a sustainable and economic choice which, if correctly designed, could significantly improve the resistance against the typical distresses of flexible pavements. For this reason, this paper aims at evaluating the mechanical properties of two asphalt mixtures modified with two plastomeric compounds through the dry method, by comparing their results with those obtained for a reference asphalt mixture modified with Styrene–Butadiene–Styrene (SBS) polymers. One of the compounds consisted of plastomeric polymers, whereas the other was made of recycled plastic and graphene. The experimental program included laboratory tests on shear gyratory compacted specimens and cores extracted from a real-scale field trial. The results showed that stiffness, fatigue and rutting resistance of the two polymeric compound modified mixtures were comparable to those of the reference mixture. Finally, a Falling Weight Deflectometer (FWD) campaign, performed in the field after one year of service life of the pavement, showed a reduced structural response of the sections constructed with compound modified mixtures with respect to the reference one because of compaction issues and possible interlayer de-bonding effects. [ABSTRACT FROM AUTHOR]

Asphalt pavement is a key component of highway infrastructures in China and worldwide. In asphalt pavement design and condition assessment, the modulus of the asphalt mixture layer is a crucial parameter. However, this parameter varies between the laboratory and field loading modes (i.e., loading frequency, compressive or tensile loading pattern), due to the viscoelastic property and composite structure of the asphalt mixture. The present study proposes a comprehensive frequency-based approach to correlate the asphalt layer moduli obtained under two field and three laboratory loading modes. The field modes are vehicular and falling weight deflectometer (FWD) loading modes, and the laboratory ones are uniaxial compressive (UC), indirect tensile (IDT), and four-point bending (4PB) loading modes. The loading frequency is used as an intermediary parameter for correlating the asphalt layer moduli under different loading modes. The observations made at two field large-scale experimental pavements facilitate the correlation analysis. It is found that the moduli obtained via laboratory 4PB tests are pretty close to those of vehicular loading schemes, in contrast to those derived in UC, IDT, and FWD modes, which need to be adjusted. The corresponding adjustment factors are experimentally assessed. The applications of those adjustment factors are expected to ensure that the moduli measured under different loading modes are appropriately used in asphalt mixture pavement design and assessment. [ABSTRACT FROM AUTHOR]

Numerous ways to use recycled asphalt (RA) in the road base course will provide both environmental and economic benefits, allowing to recycle and utilise this initially waste material in road or pavement reconstruction projects. However, the properties and parameters of RA necessary for the application of reclaimed asphalt pavement (RAP) in a new pavement structure in most cases are not detectable in the design stage, which complicates design and construction process. The purpose of this paper is to study possibilities for evaluating the performance and parameters of RA, as well as to review the possibilities, methods and applications for RA testing. Data for this case study were obtained from recently completed road structures in the form of FWD measurements, together with lab explored parameters of drilled pavement cores. Based on that data, the relationships between the main pavement structural parameters, such as modulus on the surface of the pavement, compressive strength of RA core segment, thickness of bound layers and back calculated modulus were examined. On the way to exploring different analytical approaches, two approximation models were developed and compared, using the obtained data: by directly approximating the obtained data and after processing them with artificial neural network (ANN).

The pavement deflection measured by falling weight deflectometer (FWD) detection equipment can be used to determine the bearing capacity of a pavement structure through modulus backcalculation to provide suggestions for pavement structure maintenance. However, because asphalt mixtures are temperature-sensitive materials, they are greatly affected by temperature, and changes in temperature can cause their mechanical properties to vary and affect the structural bearing capacity. Therefore, this paper conducts a pavement deflection test on an in-service highway asphalt pavement at different temperatures in different seasons. The representative temperature of the asphalt layer was determined through comparative analysis. The temperature’s effective influence distance on the deflection basin was found, and a more suitable temperature correction model for the deflection basin of asphalt pavement was established. The results showed that the temperature at the middle layer depth of the asphalt layer is more suitable as the representative temperature of the asphalt layer. The effective influence range of temperature on the deflection basin is 90 cm. The deflection change rate before and after the temperature correction at a radial distance of 20 cm is more appropriate for the temperature correction of the deflection basin.