Pavement Design Research Articles

Thermal insulation of flexible pavements utilizing foam glass aggregates to mitigate frost action in cold regions — Development of design tools

This manuscript focuses on the use of foam glass aggregates (FGAs) as insulator to protect pavements against frost action. The ultimate objective of the paper was to develop design tools for the thermal design of pavements insulated with FGAs. A mathematical model was outlined to describe the complex thermal behavior of FGAs and calculate temperature levels within a domain representing a pavement insulated with FGAs. The formulation is based on the one-dimensional heat equation which was discretized with a forward finite-difference technique and subsequently coded in Fortran90. This code was executed to successfully replicate temperature measurements collected within an experimental pavement insulated with FGAs, enabling the validation of the model. The model was then re-executed to perform three different sensitivity analyses and investigate the effects of the pavement geometry, layers humidity, and FGAs’ effective particle size on the maximal frost front penetration. Compared to a pavement without insulation, utilizing FGAs reduced the maximal frost front depth. The sensitivity analyses were summarized in design charts to guide the utilization of FGAs for the thermal design of pavements. The code utilized to generate these charts is freely available on GitHub.

Predicting the california bearing ratio via hybrid method of multi-layer perceptron

The California Bearing Ratio (CBR) holds significant importance in the design of flexible pavements and airport runways, serving as a critical soil parameter. Moreover, it offers a means to gauge the soil response of subgrades through correlation, an aspect pivotal in soil engineering, particularly in shaping subgrade design for rural road networks. The CBR value of soil is influenced by numerous factors, encompassing variables like maximum dry density (MDD), optimum moisture content (OMC), liquid limit (LL), plastic limit (PL), plasticity index (PI), soil type, and soil permeability. The condition of the soil, whether soaked or unsoaked, also contributes to this value. It is worth noting that determining CBR is time-consuming and extensive. Acknowledging the gravity of this determination, the study introduces a pioneering approach employing machine learning. This innovative technique uses a foundational multi-layer perceptron model, harnessing the algorithm’s robust capabilities in addressing regression challenges. A hybridization approach enhances the multi-layer perceptron’s performance and achieves optimal results. This approach integrates the Bonobo Optimizer (BO), Smell Agent Optimization (SAO), Prairie Dog Optimization (PDO), and Gold Rush Optimizer (GRO). The hybrid models proposed in this study exhibit promising results in predicting CBR values. The MLAO3 hybrid model is particularly noteworthy, emerging as the most accurate predictor among the range of models, with an impressive R2 value of 0.994 and an RMSE value of 2.80.

Effects of Loading and Compaction Conditions on Permanent Strains of Unbound Lateritic Soils from Senegal and Burkina Faso

Permanent strains of granular materials result from the repetitive passage of heavy trucks on the pavement. Pavement design relies mainly on permanent strains to predict rut depths. In order to contribute to the improvement of technical documents used for the design and modelling of pavements in tropical African countries, the researchers have focused on the determination of the permanent deformation parameters of laterites (axial (εp,1) and radial (εp,3) permanent strains). The Repeated Triaxial cyclic Loading (RTL) apparatus was used according to the European standard (EN 13286-7: 2004, Multistage method). Four sites of gravelly lateritic soils chosen, two from Burkina Faso (Badnogo2 and Dédougou) and two from Senegal (Sindia and Lam-Lam) were tested in this research. They are compacted to 95% and more of the optimum with a variation in water content of ±2% of the optimum. The permanents deformations are influenced by the water content, the compaction rate and the stress level. The axial permanent deformation ε1,p (max) decreases by 83.4% when the water content decreases from 12.10% to 7.59%. Moreover with a compactness rate that varies from 95.58% to 100.06%, respectively from a water content that varies from 10.04% to 9.36%, we observe a decrease in deformation ε_(1,p) from 224.340*10-4 to 148.150*10-4 from the 50,000 cycles, which shows the effect of the compactness rate and the stress level on the lateritic gravels materials soils. however, for a good control of permanent deformations on flexible pavements using gravel materials, it is necessary to compact at water contents lower than the optimum added to average compaction rates. Keywords: permanent strains (p), lateritic soils, Repeated Triaxial cyclic Loading (RTL), Sindia, Badnogo2, Dedougou, Lam-lam.

Study on biaxial bending fatigue performance of Engineered Cementitious Composites (ECC)

Structural components such as bridge deck, highway pavement and thin-walled roof dome often are subjected to the biaxial and even multi-axis stress state due to the external load. Also, the fatigue effect cannot be ignored due to the moving vehicle load in the design of these structures. If engineering cementitious composites (ECC) is used in the above traditional concrete structures, their performance, such as easy cracking and short service life can be greatly improved. However, the biaxial bending fatigue performance of ECC should be analyzed in detail. At present, the biaxial bending test methods of cement-based materials include biaxial bending test (BFT) and centrally loaded round panel test (RPT). This study used both RPT and BFT test methods to analyze the biaxial fatigue performance of ECC and used four-point bending test (4PBT) uniaxial fatigue test as a reference. The stress levels S were set as 0.5, 0.6 and 0.7. The uniaxial and biaxial bending fatigue failure procedures of ECC were analyzed by plotting the three-stage deflection development curve, the fatigue damage and strain relationship curve based on the linear cumulative fatigue damage theory, and the S–N curve. The fatigue life of ECC biaxial bending specimens was greater than that of uniaxial bending specimens. At S = 0.5, the fatigue life: BFT > RPT. At S = 0.6, the fatigue life of BFT and RPT specimens was close. At S = 0.7, the fatigue life: BFT < RPT. With increasing stress level, the fatigue life of BFT specimen decreases more than that of RPT specimen. The lognormal distribution model and Weibull distribution model were used to fit the uniaxial and biaxial bending fatigue life of ECC, respsectively. Using the double logarithmic fatigue equation, fatigue life under the failure probability PF of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 was derived. The survival rate represents the level of safety reservation, which could provide reference and basis for the design of ECC bridge deck and highway pavement with different safety reservation requirements.

Reporting the Bearing Capacity of Airfield Pavements Using PCR Index

Airfield pavements are important assets that have to secure the safe operation of an airport. On this basis, assessing and reporting the bearing capacity of an airfield runway pavement is a critical task. Recently, the Aircraft Classification Rating-Pavement Classification Rating (ACR-PCR) system has been introduced, which uses the PCR index for expressing the bearing capacity of an airfield pavement. In order to accurately determine PCR, the mechanical characteristics and the thicknesses of the individual layers of a pavement are required. For this purpose, it is not seldom that in the absence of resources dedicated to detailed pavement evaluation procedures, assumptions for the material characteristics of the pavement considering typical materials may be made, while pavement thicknesses may be derived by pavement design records. The present paper highlights the importance of using Non-Destructive Testing (NDT) for accurately assessing the in-situ condition of a flexible runway pavement and determining the PCR index. In order to achieve the goal of the investigation, measurements were performed along the flexible pavement of an airport runway. In addition, the paper focuses on the impact of the variation of the thickness and of the mechanical characteristics of the asphalt concrete layers on the PCR index and on the interpretation of the results considering the acceptance of aircraft operations by airport authorities.

Development of road pavement structures using zeolite of the Tatar-Shatrashanskoe deposit

Introduction. The growing dynamics of road construction, the active improvement of domestic road structures and technologies, and the modernization of the production base will make it possible to form a comprehensive sustainable transport framework for the country, which will provide an impact to the entire economy of the Russian Federation. One of the economically and technologically advantageous solutions for this is the development and construction of road structures using zeolite - pozzolanic additive. The analysis of Russian and foreign sources indicates that pozzolanic additives improve the physical and mechanical properties of road building materials. The purpose of the work is to develop road pavement structures using zeolite from the Tatarsko-Shatrashanskoe deposit. To achieve this purpose, the tasks such as the development of road building materials using zeolite ( local mineral materials treated with Portland cement and zeolite are used for base layers, warm asphalt concrete with zeolite is used for coating layers), the design and calculation of road pavements using zeolite from the TatarskoShatrashanskoe deposit were solved.Materials and methods. The experimental laboratory studies of materials in accordance with GOST 23558, GOST R 70396, GOST R 58406.8, GOST R 58406.9, GOST 9128, GOST 12801 were carried out. The calculation of road pavement structures in the Credo Radon software package for permissible elastic deflection, shear resistance, bending resistance, static load, frost resistance, drainage layer for climatic conditions typical of the Republic of Tatarstan, according to PNST 265, GOST R 58818 was carried out.Results. As a result of the research, the physical and mechanical properties of samples of road building materials using zeolite, which correspond to regulatory requirements were determined. The design and calculation of road pavements using zeolite in the Credo Radon software package was carried out. Structural transverse profiles of highways of categories IV and V using zeolite from the Tatarsko-Shatrashanskoe deposit have been proposed. The use of developed materials and road structures will currently improve the economy, rational environmental management of the region and, in general, provide an opportunity to improve the quality of life in cities and towns by successfully completing the five-year road activity plan.

Prediction of the Subgrade Soil California Bearing Ratio Using Machine Learning and Neuro-Fuzzy Inference System Techniques: A Sustainable Approach in Urban Infrastructure Development

In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional laboratory methods for obtaining CBR values are time-consuming and labor-intensive, prompting the exploration of novel computational strategies. This paper illustrates the development and application of machine learning techniques—multivariate linear regression (MLR), artificial neural networks (ANN), and the adaptive neuro-fuzzy inference system (ANFIS)—to indirectly predict the CBR based on the soil type, plasticity index (PI), and maximum dry density (MDD). Our study analyzed 2191 soil samples for parameters including PI, MDD, particle size distribution, and CBR, leveraging theoretical calculations and big data analysis. The ANFIS demonstrated superior performance in CBR prediction with an R2 value of 0.81, surpassing both MLR and ANN. Sensitivity analysis revealed the PI as the most significant parameter affecting the CBR, carrying a relative importance of 46%. The findings underscore the potent potential of machine learning and neuro-fuzzy inference systems in the sustainable management of non-renewable urban resources and provide crucial insights for urban planning, construction materials selection, and infrastructure development. This study bridges the gap between computational techniques and geotechnical engineering, heralding a new era of intelligent urban resource management.

Bayesian optimization algorithm based support vector regression analysis for estimation of resilient modulus of crushed rock materials for pavement design

The precise determination of the resilient modulus (MR) of the base and sub-base materials is a major preoccupation and a key criterion in the flexible pavement design process. The experimental determination of MR implies a challenging process which requires usually very difficult test procedures and extreme precautions and manpower. This is why soft computing techniques are increasingly popular and of growing importance. Many prediction techniques based primarily on linear and non-linear regression could not provide flexible use and consistent prediction of MR for practical engineering. This article introduces a hybrid of the Bayesian optimization algorithm (BOA) and support vector regression (SVR) as a new modelling tool for the MR prediction of crushed stone materials used as base and sub-base layers for pavement design. For this purpose, an experimental database was utilized to generate the hybrid BOA-SVR model of indirect estimation of the resilient modulus based on material type, basic engineering characteristics and loading conditions. The database consists of 260 experimental datasets obtained from repeated loading triaxial tests performed by the laboratory of the Central Transportation Agency located in Algiers, Algeria. To develop the model, all hyperparameters were optimised using the BOA technique. It was found that the average, median, standard deviation, minimum, maximum and interquartile range of the expected values of the developed hybrid model are very close to the experimental results. Results revealed that the hybrid BOA-SVR model predict the MR of the crushed stone materials with a coefficient of determination of 99.91% and root mean squared error of 3.55. Comparisons with traditional and other Artificial intelligence models showed that BOASVR hybrid model predictions are more accurate and robust than those of other models.

Analysis of Fixed and Variable Rigid Pavements in Comparison for Longevity, Durability and Cost-effectiveness

Urbanization has increased significantly during the last century, affecting both rural and urban areas. Due to the growing need for improved connectivity and services, roads and other transportation infrastructure are being built quickly. To meet this need, scientists, designers, and builders have been investigating novel and reasonably priced manufactured goods with the goal of streamlining the building process and improving overall robustness. In recent times, concrete pavements have witnessed a surge in popularity in India, driven by the escalating costs associated with bituminous pavement. The main benefit of using stiff pavement is that it is resilient and can hold its form even under harsh weather and traffic situations. Although concrete pavements may have a higher initial cost, they frequently wind up being more economical in the long run since they require less upkeep and have an excellent design life. This study's primary objective is to present a comparative analysis of pavement appropriateness while accounting for longevity, durability, and cost-effectiveness, among other factors. The simulation can be utilised to gain a quantitative understanding of the dynamic strains and deflections present in a rigid pavement and flexible system. It is discovered that the impact of surface roughness on a slab structure's dynamic response is significant for the pavement structure's useable life span and can be taken into consideration during pavement design. The model can be adjusted to determine the k-value needed to assess a pavement's subgrade support as it ages.

Resilient moduli characterization of cement-treated silt

The performance of a flexible pavement depends on the resilient modulus (MR) of subgrade soil. Thus, MR is a key design parameter for mechanistic-empirical pavement design of flexible pavements. Generally, the resilient modulus is determined by conducting repeated load triaxial (RLT) tests in the laboratory and has been used to characterize the subgrade soil behavior under repeated traffic loading conditions. The use of cement to stabilize natural subgrade soils is widely accepted by transportation agencies. Several research studies were conducted on the resilient behavior of cementtreated soils. However, limited research studies have been conducted on the resilient behavior of cement-treated silty soil. Therefore, the current research study assessed the resilient moduli properties of cement-treated silt. Cement-stabilized soil specimens were statically compacted and cured in a humid room for a stipulated curing period before conducting RLT tests. RLT tests were conducted on cement-treated specimens at different cement dosages and curing periods to study the effect of the cement dosage and curing time on the resilient modulus. Test results indicated that a significant improvement in performance was observed after cement treatment. The untreated soil specimens exhibited stresssoftening behavior with an increase in deviator stress, whereas the cement-treated specimens exhibited stress-hardening behavior. The resilient modulus was increased with an increase in cement dosage. Regression analyses were conducted on RLT test results using three-parameter universal model and model parameters were determined. It was observed that the three-parameter universal model exhibited an excellent fit with experimental data.

The effect of RAP content on fatigue damage property of hot reclaimed asphalt mixtures.

The fatigue property of the recycled mixture affects the structural design of recycled pavement. In order to explore the effect of different reclaimed asphalt pavement (RAP) content on the fatigue properties of recycled mixtures, the fatigue properties of recycled mixtures were analyzed through an indoor fatigue test and finite element numerical simulation. Based on the phenomenological method and the dissipated energy theory, the fatigue properties of recycled mixtures with different RAP contents were analyzed and the fatigue damage of the mixtures were also studies under various strain levels. Based on the finite element numerical model of fatigue damage, the stress distribution and internal damage field distribution of trabecular specimens under different temperatures, strain levels and RAP contents were analyzed. The results showed that the anti-fatigue level of the mixture decreased as the RAP content was increased. The relative change rate of dissipated energy for different types of mixtures showed a two-stage change rule with the change of load times, that is, the value is large and decreasing, and the value is small and stable. The correlation between the plateau value (PV) and the fatigue life was established under the double logarithm coordinates, which could better analyze the influence law of the RAP content on the fatigue performance of the recycled mixture. Under different temperatures, strain levels, and RAP contents, the stress at the bottom of trabecular specimen and the overall damage field were mainly generated at the upper part under compressive stress and the bottom under tensile stress, and the damage field distribution area accounted for a small part of the whole specimen. According to the test results and fatigue damage distribution, it is recommended that the content of recycled aggregate in recycled asphalt mixtures be less than 30% to ensure good performance. The research results have important practical significance for the improvement of fatigue performance and engineering application of recycled mixtures.

PERFORMANCE EVALUATION OF LATERITE AND PULVERIZED RECLAIMED ASPHALT PAVEMENT STABILIZED WITH BASE SEAL AND CEMENT

This research delves into the effectiveness of incorporating pulverized Reclaimed Asphalt Pavement (RAP), Base Seal, and cement to enhance the stability of lateritic base materials in Nigeria. Addressing a crucial gap in pavement engineering literature, particularly the underexplored use of base seals as liquid stabilizers, the study adopts a comprehensive methodology involving literature review, field evaluation, and laboratory tests. Analyzing various material mixes, from pure Laterite to combinations with RAP, Base Seal, and varying cement contents, the research reveals substantial improvements in crucial engineering properties. Enhanced particle size distribution, reduced clay content, and optimal compaction characteristics at 0% cement content for laterite materials with pulverized RAP signify the positive impact of these additives. California Bearing Ratio analysis establishes a consistent correlation between higher cement content and improved load-bearing capacity. Notably, the synergistic effects of RAP and base seal, particularly at 5% cement content, showcase the highest CBR value (91), indicating optimal conditions for strength and stability. The study concludes with practical recommendations for road maintenance authorities, advocating for innovative approaches like full-depth reclamation techniques and stabilized full-depth reclamation, exploring different RAP to base material ratios, examining curing periods' impact, assessing long-term performance, considering environmental implications, and conducting field trials for validation. Overall, these findings contribute valuable insights to pavement design practices, fostering the development of resilient infrastructure in construction projects.

Comparison of road damage analysis using PCI method and Bina Marga method and the analysis of road improvement methods using the road pavement design manual (Case study: Citayam – Parung road)

The Citayam - Parung road section is an inter-district and city route between Bogor Regency and Depok City, West Java Province, on this road section there is high mobility. This research aims to determine the type of road damage using the PCI method and Bina Marga method and analyze repairs using the 2017 MDP. Data collection was carried out by direct survey and interviews with related agencies. The results of the research analysis of damage to the Citayam - Parung road are alligator cracking, block cracking, edge cracking, transverse longitudinal cracks, utility patches and excavations, polished aggregate, photoles and weathering and raveling. The PCI method damage analysis has a value of 71.96 with Very Good pavement quality, and the results of the Bina Marga method damage analysis have a priority order of 10 with the priority order of the Routine Maintenance Program. The relationship between the PCI method is directly proportional to the Bina Maarga method, with a PCI value between 71-85 and the priority order for Bina Marga, namely 10, the regression equation obtained is PCI = 207.52 – 13.296*(BM). The results of the repair analysis are a 45 mm thick non-structural overlay with an estimated cost of Rp. 2,404,076,800.00.

Analysis of Guiding Function in Park Pavement Design—Taking Jinan Ribbon Park as an Example

Analysis of Guiding Function in Park Pavement Design—Taking Jinan Ribbon Park as an Example

Contribution to the Characterization of Laterites Developed on Granitic Rock in Mbanga (Littoral-Cameroon): Significance in the Sustainable Pavements Design

Contribution to the Characterization of Laterites Developed on Granitic Rock in Mbanga (Littoral-Cameroon): Significance in the Sustainable Pavements Design

Design and validation of a regression model for soil resilience modulus applied in empirical-mechanistic pavement design

RESUMO O aparecimento precoce de problemas na estrutura dos pavimentos e o não cumprimento do horizonte de projeto não só provocam desconforto aos usuários devido às más condições de rolamento e a falta de segurança durante o tráfego, como também demandam uma maior quantidade de matéria-prima e capital para restauração, recuperação ou reconstrução das estruturas danificadas. Os métodos de dimensionamento de pavimentos flexíveis empíricos-mecanísticos, como o novo método brasileiro de dimensionamento (MeDiNa), consideram o comportamento mecânico das camadas e do pavimento como um todo e representam de maneira mais apropriada a relação existente entre as cargas solicitantes do tráfego e a resposta apresentada pelo pavimento. O MeDiNa faz uso dos parâmetros de rigidez, como o módulo de resiliência (MR), para realizar uma análise elástico-plástica da estrutura. Este parâmetro, por sua vez, sofre algumas limitações de uso, visto que é obtido em laboratório por meio de ensaios triaxiais dinâmicos que exigem a utilização de equipamentos complexos, mão de obra especializada, além de demandar uma quantidade significativa de material e apresentar uma difícil implementação em situações práticas, tornando a execução do ensaio restrita fora das universidades e instituições acadêmicas. Tendo em vista esta problemática, este artigo propõe um modelo neural de regressão para previsão do módulo de resiliência obtido através dos parâmetros geotécnicos básicos e usuais. Ademais, para comprovar a viabilidade do modelo gerado, foram realizadas simulações considerando os diversos tipos de vias, bem como os modelos constitutivos elásticos do solo linear e não-linear. Demonstrando, assim, que se trata de um modelo satisfatório para previsão do módulo de resiliência, que poderá ser empregado tanto em rodovias com volumes de tráfego moderado quanto emvolumes elevados, quando não for possível a realização do ensaio.

Laboratory Evaluation of Marginal and Industrial Waste Material in Geocell-Reinforced Pavements under Cyclic Loading

Abstract The availability of quality materials for the construction of pavements has been a problem in some regions. This scarcity enforced geosynthetic materials as one of the quests for su1stainability in the pavement industry. This study attempted to stabilize marginal (tunnel muck, reclaimed asphalt pavement material) and industrial waste (zinc slag) materials by employing high density polyethylene geocell to appraise the effectiveness of geosynthetic reinforcement in enhancing the characteristics of pavement materials and mitigating their rutting. The cyclic plate load tests are performed on marginal and industrial waste material with geocell-reinforced and unreinforced base layers over black cotton soil as the subgrade. The tests were conducted following the trapezoidal loading pattern with a 0.77-Hz frequency. The geocell-reinforced pavement performance was evaluated for resilient deformation, accumulated permanent deformation, rut depth reduction, traffic benefit ratio, and base layer thickness reduction. The mechanistic empirical pavement design guide (MEPDG) permanent deformation performance (PDP) model framework was used to predict the accumulated permanent deformation in unbound granular layers and to differentiate the rutting performance in geocell-reinforced and unreinforced sections. This study determined the material constants of the MEPDG PDP model for marginal and industrial waste materials used in the pavement section for quantifying the reduction in base layer thickness.

Assessment of Surface Layer Characteristic on Flexible Pavement Design Life

The surface, a layer directly under tire load, is often made of crushed aggregate, gravel, or recycled materials. In order to extend the operational lifetime of the road, the surface serves as higher properties of materials. The impact of performance for the surface layer on the design life was examined in this research. Employing the KENPAVE software, the study examined the impact of changing the thickness of the surface layer (2″, 2.5″, and 3″) and the resilient modulus (300, 400, and 500 ksi) on the expected service life of the flexible pavement for both repeated loads 30000 and 40000. The results show that the increased surface layer thickness lead to the increase in pavement design life for all resilient modulus and both repeated loads. The percentage of increase of design life of pavement grew as the resilient modulus grew (for all repeated loads). As resilient modulus of surface layer increased, so did the pavement design life increase. The percentage of increasing the design life of pavement results from increased resilient modulus was increased with the increasing thickness layer. The percentage of improvement the design life of pavement caused by increase of resilient modulus, increase with increase the surface layer thickness (for all repeated loads).

Measurement of subgrade soil permanent deformations under repeated loadings during simple in-situ test

is well known that permanent deformation has a significant influence on the performance of pavements because it leads an increase in maintenance operations and costs and reduces ride quality. Therefore, it is important to predict the permanent deformations during the design stage. Due to the fact that up to date there is no simple test equipment and procedure that enables a direct in-situ measurement permanent deformations of subgrade soil under repeated loading, the current research has been undertaken to evaluating new testing approach to fulfil this requirement. The current study deals with developing a new multifunctional light weight deflectometer (LWD) that can be used to determine the in-situ permanent deformations of subgrade soil due to repeated loading by simple, cheap and time saving testing approach. It was concluded that the suggested repeated light weight deflectometer test could give a powerful material assessment and pavement design tool for the analysis of compacted subgrade soil used in this study. The developed LWD that can measure the permanent deformations directly could be utilized to establish the risk level of permanent deformations in subgrade soil in pavement constructions during the design and construction stages.

Full-scale accelerated load testing of a new mechanised cement bound macadam (MCBM) pavement

The purpose of the research is to define and describe the performance behaviour during full-scale accelerated loading for a new heavy duty pavement type referred to as Mechanised Cement Bound Macadam (MCBM). MCBM is a cost-effective and reduced carbon footprint alternative to structural asphalt concrete and conventional concrete pavements. Four MCBM test sections were constructed with two key considerations in mind, the influence of layer thicknesses and maximum stone size within the gradation. In addition, defining the fundamental strength behaviour of the pavement, the failure mechanisms and their impact on perpetual pavement design were key objectives for the research. Dynamic and semi-static deflection measurements, strain measurements from strain gauges embedded in the pavement, crack mapping and transverse surface profile were collected at intervals throughout the accelerated loading. Performance testing showed that the stone interlocked structure is unique and undergoes multiple strength phases, enabling excellent shear and rut resistance by upholding vertical load bearing. The accelerated load testing also proved that significant structural strength remains post-bound phase. However, the MCBM design is based on a bound phase criterion and specifies a threshold fatigue stress value less than 30% of the flexural strength (breaking strength under four-point beam testing). Hence, the MCBM is perpetual by design and intended to function in the bound phase, requiring only intermittent resurfacing.