Deflectometer Research Articles

Nonlinear Interpretation of Resilient Modulus Parameters Considering Incremental Static and Dynamic Loading

The resilient modulus ( Mr) is typically interpreted as the average of the last five secant slopes of the cyclic stress-axial resilient strain curve from repeated loading triaxial tests. It is not uncommon to then fit mathematical models to the secant Mr to derive model parameters ( Ki, more commonly known as K1, K2, and K3) that are then used in pavement analysis. Some engineers also backcalculate Ki from a falling weight deflectometer test. Many researchers use an incremental loading procedure to analyze pavements. When doing so, it is important to consider the nonlinear load-deformation behavior, which is considered only coarsely in the secant slope approach. Some incremental loading procedures assume the geomaterial to be nonlinear elastic while a dynamic finite element analysis typically assumes the geomaterials to be nonlinear and viscoelastic, that is, having springs and dashpots. With the latter, additional damping parameters to represent the viscoelastic effects are required. This paper compares Ki parameters estimated using linear regression on a log transformation of the Mechanistic–Empirical Pavement Design Guide (MEPDG) Mr model, which is a non-viscoelastic secant Mr approach, with those obtained using nonlinear regression of the time dependent deformations when interpreting the Mr test using incremental loading of a: 1) nonlinear elastic geomaterial; and 2) nonlinear viscoelastic geomaterial with inertial mass. The results show that the estimated Ki parameters governing the geomaterial nonlinearity are substantially affected by the estimation method and that the second alternative approach can model hysteresis well.

Perencanaan Tebal Overlay dengan Alat Benkelman Beam dan Falling Weight Deflectometer

In a certain period, the road pavement will be damaged so this pavement needs to be overlay. There is pavement damage that needs overlay activity in the highway, so the pavement is needed to maintain. This study is performed to find the overlay thick of pavement (overlay) by using Falling Weight Deflectometer (FWD) and Benkelman Beam (BB) tools. Overlay thick design is based on Design of Overlay Thick of Flexible Pavement by Deflection Method (Pd T-05-2005-B). The segment of this study is in Jalan Banda Aceh - Medan highway, the data that taken is from the same point between Falling Weight Deflectometer (FWD) and Benkelman Beam (BB). To design the thickness, this investigation needs the result deflection of Falling Weight Deflectometer (FWD) and Benkelman Beam (BB), then the value result is corrected. After the obtain corrected deflection value, the next process is calculating uniformty factor (FK), representative deflection (Dsbl ov), design deflection (Dstl ov), overlay thick (Ho), factor of overlay thickness (Fo), and corrected overlay thick (HT). The result of this study is the overlay thick from Falling Weight Deflectometer (FWD) and Benkelman Beam (BB), it is 5,235 cm for Falling Weight Deflectometer (FWD) and 3,722 cm for Benkelman Beam (BB). The result difference between Falling Weight Deflectometer (FWD) and Benkelman Beam (BB) is 1.513 cm or 28.90% in the percentage.

Adaptation of an alternative neural network instead of ANN for backcalculating pavement layer moduli

The structural condition of the pavement is often evaluated using deflection data from the non-destructive test such as the Falling Weight Deflectometer (FWD). Young's moduli calculated from surface deflections are used to characterize pavement layers. One of the most popular techniques for analyzing FWD data to determine pavement layer moduli is backcalculation. Artificial Neural Network (ANN) has been explored or used in studies to backcalculate layer moduli from FWD data, although its applications in this area are relatively recent. However, ANN suffers from limitations in terms of convergence accuracy and generalization capability. This research aims to develop an alternative neural network instead of ANN for backcalculating pavement layer moduli. Based on FWD data, Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) networks were used to overcome the shortcomings of the traditional ANN. The LSTM, RNN, and ANN networks were developed and trained with the same training properties. The results revealed that LSTM attained high convergence accuracy and fastest convergence speed than ANN and RNN. LSTM network produced reasonable and accurate layer moduli values with determination coefficient (R2) of 0.9298 when compared to the measured values, while R2 values of the RNN and ANN networks were 0.906 and 0.8326, respectively. There was evidence that the LSTM network can learn the continuity pattern between the deflection basin points and enhance the FWD backcalculation accuracy.

Optimizing Geotechnical Data Input Based on Light Weight Deflectometer for Road Design and Performance Analysis

This study explores alternative methods for assessing critical parameters in pavement design, specifically Young’s modulus and Poisson’s ratio. While repeated load triaxial testing is traditionally used, its high cost and time requirements drive the search for more efficient methods. Falling weight deflectometer tests are also resource-intensive, leading to the investigation of light weight deflectometer tests. Utilizing EraPave software for analysis, which employs a multi-layer elastic theory back-calculation tool, the research examines material properties through laboratory tests on unbound granular material, sandy soil, silty sand soil, and sandy silty clay soil, providing data for field tests. Field LWD tests, conducted under various moisture contents and dynamic loads, provided data processed through EraPave to predict layer moduli. Results demonstrate LWD’s effectiveness in predicting layer moduli for different construction materials. Despite variations in root mean square error values, LWD data consistently align well with EraPave predictions, underscoring its reliability for pavement evaluation. Case studies illustrate LWD and EraPave’s adaptability to different moisture contents and stresses. This study advocates for LWD tests’ efficiency and highlights the importance of analytical tools like EraPave for accurate pavement assessments, contributing to optimized pavement evaluation processes and informed road construction and maintenance decisions.

Unraveling the optimal strategies for asphalt pavement longevity through preventive maintenance: A case study in South Korea

This study provides a comprehensive evaluation of three pavement surface treatments—Re-Ascon, Micro-surfacing, and Fog-seal—aimed at enhancing the longevity of asphalt concrete pavement. Utilizing visual inspection, bearing capacity measurements, and linear regression modeling, this study rigorously assesses the effectiveness of these strategies in real-world road environments. Notably, Re-Ascon emerges as the least damaged method in visual inspection, offering crucial insights into initial pavement conditions. Visual inspections consistently underscore Re-Ascon's outstanding performance in mitigating pavement distress, particularly in addressing cracking. Quantitative analysis using the Surface Curvature Index (SCI) from Falling Weight Deflectometer (FWD) measurements highlights Re-Ascon's superior elastic modulus (E1) and resistance to deflection compared to alternatives. Re-Ascon's 20 % SCI reduction compared to Fog-seal highlights its superior deflection resistance, supported by logarithmic elastic modulus values. Correlation analysis confirms Re-Ascon's resilience, maintaining low SCI even under higher loads and adverse weather conditions. Geographical variations and method-specific influences are revealed through PCI analysis, emphasizing the vital impact of preventive maintenance. The identified PCI threshold of 60 % guides timely interventions for major maintenance, while service life analysis forecasts approximately 3.0, 2.5, and 1.5 years for Micro-surfacing, Re-Ascon, and Fog-seal methods, respectively. In conclusion, this research furnishes critical insights into preventive maintenance methods, advocating a holistic assessment through visual, structural, and predictive perspectives, and emphasizing the need for ongoing research to advance sustainable strategies.

Back to the future: Retrograde alcohol calculations an uncertain science

Retrograde extrapolations, known as back calculations are widely used in forensic toxicology to estimate the blood alcohol concentration of an individual at some prior time. In the UK guidelines have been issued by the United Kingdom and Ireland Association of Forensic Toxicologists) and the Organization of Scientific Area Committees (OSAC) for Forensic Science. However, these guidelines are not fully agreed and open tointerpretation. Alcohol elimination rates have been discussed in numerous publications since Widmark’s original data was published. The current guidance from UKIAFT, is to report the most likely back calculated result together with a range of results based on the 95% confidence limit elimination rates (9 to 29 mg/100 mL/hour).The Divisional Court, upheld by the House of Lords, ruled that in order to convict someone for being over the prescribed limit on the basis of any back calculation, the case must be proven beyond reasonable doubt. A 99.73% confidence interval increased to 3 standard deviations at the lower end would provide a greater factual basis for the court and cover alarger proportion of the population, this can be achieved by increasing the elimination range to 8 to 29 mg/100 mL/hour. Retrograde extrapolations also rely on the subject being post absorptive at the prior time. In the UK, back calculations are validif the subject has not eaten or consumed alcohol withinonehour ofthe back calculation time. Where the subject has eatenprior to the back calculation, experts are instructed to consider whether the back calculation is applicable. In Germany and the United States back calculations are not permitted to a time within 2 h after last drink consumed. The 2 h limit would better meet the highest standard of ‘beyond reasonable doubt’ burden of proof, and should be used. These proposed changes would decrease the uncertainty associated with retrograde calculations carried out by UK toxicologists.

Remote sensing of eruptions and transport of Taal volcano in January 2020

The eruption and transport of the Taal volcano (14 N, 121 E) in January 2020 have been investigated using remote sensing measurements of several satellites, including the Moderate Resolution Imaging Spectroradiometer, Ozone Monitoring Instrument (OMI), Ozone Mapping and Profiler Suite, and Himawari-8. The aerosol optical thickness (AOT), angstrom exponent (AE), and column densities of sulfur dioxide (SO2) derived from satellites are analyzed in this study. The ground-based AERONET data of Manila city and OMI SO2 are studied to validate high AOT events. Our findings indicate that ash and gases followed opposite transport paths. This differential transport is consistent with various wind data, HYSPLIT back and forward trajectory calculations, and emission dispersion models. The potential influences of deposition on ocean biology and climate are also discussed.

Studying the Structure of the Road Pavement and Specifying the Repair Method

Studying the structural condition of road pavement is essential for making effective decisions about the type of maintenance or rehabilitation that will be carried out on a pavement section. Reliable quantitative assessment of the volume of necessary repairs will ensure the performance characteristics and durability throughout the entire service life at minimal cost. This article presents detailed results from Falling Weight Deflectometer (FWD) and Ground Penetrating Radar (GPR) studies. In addition, an analysis of these results and recommendations for strengthening the road pavement for the Sh-176 “Sighnaghi-Saint Nino Monastery” road to develop rehabilitation and maintenance scenarios. FWD results combined with road pavement layer thickness and traffic load information to determine residual service life and necessary treatment type. Thus, using the nonlinear theory of layered halfspace elasticity, pavement structure analyzed in the same way as other civil engineering structures.

Evaluating the influence of volumetric properties on back-calculated asphalt layer moduli using falling weight deflectometer data

The back-calculation process performed in pavement systems is the numerical analysis of captured deflections to estimate layer stiffness parameters. Prediction of fatigue performance in terms of back-calculated asphalt layer moduli by using a Falling Weight Deflectometer (FWD) has specific challenges in terms of testing protocol, skillset, and complex back-calculation analysis. The performance of the asphalt layer is primarily governed by extrinsic parameters such as temperature, vehicular transient loading characteristics, moisture content, and intrinsic parameters such as binder properties and aggregate mix properties. The role of volumetric properties of asphalt mixes contributes significantly to the back-calculated asphalt layer moduli in terms of the overall life of the structure. The asphalt layer moduli value is dependent on the traditional volumetric properties of asphalt mixes such as air voids in the mix, voids in mineral aggregate, and the percentage of bitumen mix. In this study, a total of 60 in-service pavement sections are identified from three different categories of roads to perform FWD tests and collection of asphalt layer core samples. A detailed laboratory investigation has been carried out to estimate the volumetric properties of different core samples. This study uses field investigations to determine the degree of interdependency between the volumetric characteristics of asphalt mixtures and temperature on the back-calculated layer moduli. Furthermore, the findings from this study are utilized to establish several correlations at the aggregate level, demonstrating strong relationships with R2 values ranging from 0.84 to 0.875. The developed model is validated and depicted in good agreement with the actual values.

Erosion Potential of Stabilized Support Layers for Concrete Pavements and Overlays

The performance of concrete pavements and overlays is highly dependent on the uniformity, durability, and stability of the underlying support layers. Erosion of support layers can lead to pavement distresses and a reduction in pavement life. A review of existing erodibility performance tests that assessed stabilized support layers was first conducted to identify and evaluate their suitability for adaptation. The Hamburg wheel tracking device (HWTD) test was selected to assess the erosion potential of asphalt and cement stabilized support layers. Field testing with distress surveys, falling weight deflectometer, and coring was completed to obtain HWTD specimens and link laboratory results to pavement performance. The HWTD test was performed on cores obtained from in-service cement and asphalt stabilized support layers, a cold in-place recycling (CIR) mixture, and cement stabilized laboratory mixtures. As expected, an increase in cement content within cement stabilized mixtures decreases the likelihood of erosion with the HWTD. Additionally, conventional asphalt stabilized base layers were highly erosion resistant. Erosion resistant cement stabilized bases (including full-depth reclamation) should target an average HWTD erosion depth ≤2 to 4 mm (0.08 to 0.16 in.) after 10,000 load cycles based on the functional classification and expected traffic volume of the pavement section. Likewise, asphalt stabilized bases (including CIR and support layers for concrete overlays) should target an average HWTD erosion depth ≤12.5 mm (0.5 in.) after 7,500 load cycles with performance grade 64 binder.

Enhancing Falling Weight Deflectometer (FWD) Testing: Comprehensive Review and Development of Robust Procedure in the United States

Enhancing Falling Weight Deflectometer (FWD) Testing: Comprehensive Review and Development of Robust Procedure in the United States

Conversions of viscoelastic deflections of asphalt pavement under TSD load to elastic ones for pavement condition assessments

The Traffic Speed Deflectometer (TSD) facility has gained popularity in assessing asphalt pavement conditions due to its efficient testing process and minimal disruption to traffic flow. Current applications of TSD test results resemble those developed for the Falling Weight Deflectometer (FWD) test results, such as analysing the deflection basin shape and back-calculating the pavement layer modulus. However, the TSD facility induces more viscoelastic pavement deflections compared to FWD, primarily due to its rolling load. This research focuses on converting TSD’s viscoelastic deflections under a wider range of loading conditions into elastic deflections under FWD load. This conversion aims to facilitate the use of FWD-based approaches for analysing TSD deflection data. The findings indicate that the converted TSD deflections generate more reasonable evaluation results, further emphasizing the necessity of converting TSD deflections to elastic ones. The models proposed in this research serve as valuable references for performing the viscoelastic-elastic deflection conversion.

Deflection and Elastic Modulus Assessment of Subgrade in Flexible Pavement mixed with Waste Tire Scrap Material

This study aims to assess the deflection and elastic modulus (Es) of subgrade in flexible pavements, focusing on a comparative analysis between pavements with clayey soil subgrade and subgrade modified with tire scrap. The research utilized Falling Weight Deflectometer (FWD) for measuring subgrade deflection, essential in evaluating pavement performance. The FWD applied a dynamic load to the pavement, with deflection measurements processed using the KGP-BACK software to calculate the Es of the pavement subgrade. This approach included assessing the Lower Layer Index (LLI) and Es of the subgrade. Findings revealed a notable reduction of 37.5% in deflection and 2.68 times increase in Es for the tire scrap modified subgrade pavement compared to the standard clayey soil subgrade pavement. These results demonstrate significant enhancements in pavement structure, underlining the potential of recycled materials in sustainable civil engineering practices.

Improved Wave Equation Analysis for Piles in Soil-Based Intermediate Geomaterials with LRFD Recommendations and Economic Impact Assessment

The Wave Equation Analysis of Pile Driving (WEAP) has been widely used to determine drivability, predict static resistance, and assure the integrity of piles in soils. Assigning static and dynamic properties of Soil-based Intermediate Geomaterials (S-IGMs) remains a challenge in WEAP, partly attributed to IGMs that act as transition geomaterials between soil and hard rock. Furthermore, reliable static analysis methods for unit resistance predictions are rarely available for driven piles in S-IGMs in the default WEAP method. To alleviate these challenges, this study presents improved WEAP methods for steel piles driven in S-IGMs, including proposed damping parameters and Load and Resistance Factor Design (LRFD) recommendations based on newly developed static analysis methods and the classification of S-IGMs. A back calculation approach is used to generate the appropriate damping parameters for S-IGMs for three distinct subsurface conditions utilizing a database of 34 steel H- and pipe piles. Newly developed WEAP and LRFD procedures are also recommended. Additional independent 22 test pile data are used to compare and evaluate the accuracy and efficiency of the proposed WEAP methods with the default WEAP method. Compared with the default WEAP, bearing graph analysis results revealed that the selected proposed WEAP method, on average, reduces the underprediction of pile resistances by 6% and improves the reliability with a 43% reduction in the coefficient of variation (COV). Calibrated resistance factors for the proposed WEAP method increase to as high as 0.75 compared to the current AASHTO recommendation of 0.50. An economic impact assessment reveals that the proposed WEAP method is more efficient than the default WEAP method as the average difference in steel weight for 32 test piles is 0.06 kg/kN, almost close to zero, reducing the construction challenges in the current engineering practice.

Experimental study on progressive interfacial mechanical behaviors using fiber optic sensing cable in frozen soil

Frost heave and thaw settlement in cold regions pose a significant threat to engineering construction. Optical frequency domain reflectometry (OFDR) based on Rayleigh scattering can be applied to monitor ground deformation in frozen soil areas, where the interface behavior of soil-embedded fiber optic sensors governs the monitoring accuracy. In this paper, a series of pullout tests were conducted on fiber optic (FO) cables embedded in the frozen soil to investigate the cable‒soil interface behavior. An experimental study was performed on interaction effects, particularly focused on the water content of unfrozen soil, freezing duration, and differential distribution of water content in frozen soil. The high-resolution axial strains of FO cables were obtained using a sensing interrogator, and were used to calculate the interface shear stress. The interfacial mechanical response was analytically modeled using the ideal elasto‒plastic and softening constitutive models. Three freezing periods, correlating with the phase change process between ice and water, were analyzed. The results shows that the freezing effect can amplify the peak shear stress at the cable-soil interface by eight times. A criterion for the interface coupling states was proposed by normalizing the pullout force‒displacement information. Additionally, the applicability of existing theoretical models was discussed by comparing the results of theoretical back‒calculations with experimental measurements. This study provides new insights into the progressive interfacial failure behavior between strain sensing cable and frozen soil, which can be used to assist the interpretation of FO monitoring results of frozen soil deformation.

Development of a prediction model of dynamic deflections for asphalt pavements under FWD impulse loading

Pavement deflections are critical indicators in pavement design and acceptance programs. Falling weight deflectometer (FWD) technique has been widely adopted to measure the dynamic deflections in pavement engineering. Although the dynamic effect of FWD impulse loading on deflections is significant, FWD deflections are still commonly interpreted and examined using the static analysis programs in acceptance projects because of their ease of implementation and high computational efficiency. This may lead to an inability to effectively control the construction quality of pavements. Accordingly, this study aims to propose a simple and accurate approach for converting static deflection to dynamic deflection. Layered elastic theory (LET) and spectral element method (SEM) were adopted to generate the theoretical static and dynamic deflection databases, respectively. Based on the databases, a simple approach is proposed to predict the dynamic deflection only using four static deflections. The proposed approach shows lower computational workload and higher accuracy than other traditional formula forms which include equivalent layer moduli and thicknesses. In the field engineering cases, the calculated static deflections can be 2 ∼ 3 times higher than the measured ones, while the predicted dynamic deflections from the proposed approach match the theoretical dynamic deflections well and are comparable to the measured deflections for both asphalt pavements with asphalt binder or inorganic binder bases and granular bases. This indicates that dynamic deflections can more effectively control the construction quality of asphalt pavements in the FWD deflection-based design program. Meanwhile, the drawbacks of traditional prediction methods are investigated and evaluated. The proposed approach exhibits simpler form and higher accuracy, while avoiding the drawbacks of traditional methods. Combining with the common static LET-based programs, the proposed approach provides a more reasonable and practical way for the construction quality acceptance of asphalt pavements using FWD data.

Study on fatigue performance of asphalt mixture in service life based on accelerated loading test

To further study the fatigue damage evolution law of asphalt mixture in service period, the accelerated pavement testing (APT) of graded gravel base asphalt pavement and in-situ pavement was conducted. The full-scale test road of graded gravel base asphalt pavement was built, and the mechanical response sensors and temperature sensors were embedded. The fatigue damage test of the full-scale test road was conducted at 15°C through the accelerated loading test (ALT) equipment. The mechanical responses under the repeated wheel loadings were captured by the strain sensor at the bottom of the asphalt layer, and the deflections of the pavement under different cycles of wheel load were tested by Falling Weight Deflectometer (FWD). The fatigue damage model of asphalt mixture was established, and the accuracy of the model was verified by the accelerated loading fatigue test of in-situ pavement. The results show that asphalt layer bears an alternating effect of tensile and compressive strain, and when the wheel load is reduced or the driving speed increases, the tensile strain at the bottom of the asphalt layer decreases. As an evaluation index of fatigue damage of asphalt layer, the residual modulus ratio can accurately characterize the cumulative degree of fatigue damage. The modulus of asphalt layer shows an inverse S-type curve with the repeated wheel loadings. Based on the quantitative analysis of the whole process of fatigue damage of asphalt layer, a nonlinear damage evolution model of modulus attenuation of asphalt mixture was established, which would provide a reference for the study of pavement service performance attenuation law in different climatic environments and structural compositions in the future.

Experimental Monitoring of Dynamic Parameters of the Sub-Ballast Layers as a Prerequisite for a High-Quality and Sustainable Railway Line

Monitoring dynamic load transfer from train traffic to sub-ballast layers is crucial for verifying the reliability and safety of railway lines, assessing the design cost-effectiveness and achieving minimum environmental impact. For this purpose, measurements in labs, in situ or modeling the influence of dynamic loads on the immediate and long-term roadway quality are often performed using suitable software. The available test sections enabled monitoring of the dynamic loads and optimizing the critical spots where increased dynamic effects from railway traffic may occur. The subject of this paper is the calibration of the sensors installed in the different test sections of the trans-European corridor number V. As a result, the necessary input parameters for the subsequent numerical modeling of the dynamic effects on the track substructure and vibration propagation on the available sections of the upgraded railway line were obtained. The sensor calibration was carried out on the experimental field, part of the Experimental Basis of the Department of Railway Engineering and Track Management. As part of the calibration, the sensitivity of the sensors embedded in the track bed to the applied dynamic loads resulting from the impact effects of the lightweight deflectometer was assessed. The result of the calibration was the demonstration of sufficient sensitivity of the sensors and their suitability for implementation in an actual railway track structure, with the aim of obtaining relevant values of the response of the sub-ballast layers to dynamic loads and assessing the operational impacts on the sustainable environment. Also, the main result of the research was the possibility of using the theoretical–experimental route to optimize the layers of the railway body.

Effect of synthesized warm mix additive and rejuvenator on performance of recycled warm asphalt mixtures

In this study, a warm mix additive (composed of diamine and fatty acid amine) and a rejuvenator (consisting of styrene-butadiene-styrene and aromatic elements) were synthesized to facilitate the incorporation of 50% recycled asphalt pavement (RAP) in warm mix asphalt for the surface layer and 100% RAP in cold asphalt mixtures for the base layer. The effect of WMA and rejuvenator-modified asphalt binder was performed through rotation viscosity, dynamic shear rheometer, and bending beam rheometer. Simultaneously, the performances of RAP-modified asphalt mixtures were assessed using dynamic modulus, overlay test, and flow number test. Constructing two testbed roads provided a real-world evaluation of two surface mixtures and two base mixtures. The results indicated that modifying asphalt binder PG 64–22 with 2.0% warm mix additive (WMA) and 5.0% rejuvenator upgraded the performance grade to PG 76–22, significantly improving rutting resistance, and reducing 40% creep stiffness. The asphalt mixture with 50% RAP, modified with WMA and rejuvenator, demonstrated a better resistance to rutting and low-temperature cracking compared to the original mixture. Both surface and base mixtures met field application specifications, exhibiting excellent performance after a year of service, as confirmed by pavement condition surveys, and falling weight deflectometer tests, thus highlighting the potential for sustainable and high-performance recycled asphalt solutions in road construction.

Modified Asphalt with Graphene-Enhanced Polymeric Compound: A Case Study

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.