Bearing capacity of circular footings on multi-layered sand-waste tire shreds reinforced with geogrids

The presence of waste tires poses an environmental challenge as they occupy a significant amount of land and are expensive to dispose in landfills.However,reusing waste tires can address this issue when waste tires are used in geotechnical applications.To determine the viability of this approach,laboratoryscale tests were conducted to investigate load-bearing capacity of circular footings on sand-tire shred(STS)mixtures with shredded waste tire contents of 5%e15%by weight and three different widths of shreds.The investigation focused on analyzing the thickness of layers composed of STS mixtures,the soil cap,and the impact of geogrids on bearing capacity.The results indicate that a specific mixture of sand and tire shreds provides the highest footing-bearing capacity.In addition,the optimal shred content and size were found to be 10%by weight and 2 cm×10 cm,respectively.Furthermore,for a given tire shred width,a particular length provides the largest bearing capacity.The results agree well with that of previous research conducted by the first author and his colleagues in direct shear and California bearing ratio(CBR)tests.The primary finding of this research is that the use of two-layered STS mixtures reinforced by geogrids significantly enhances the bearing capacity.

Predicting the International Roughness Index of JPCP and CRCP Rigid Pavement:A Random Forest(RF)Model Hybridized with Modified Beetle Antennae Search(MBAS)for Higher Accuracy

To improve the prediction accuracy of the International Roughness Index(IRI)of Jointed PlainConcrete Pavements(JPCP)and Continuously Reinforced Concrete Pavements(CRCP),a machine learning approach is developed in this study for the modelling,combining an improved Beetle Antennae Search(MBAS)algorithm and Random Forest(RF)model.The 10-fold cross-validation was applied to verify the reliability and accuracy of the model proposed in this study.The importance scores of all input variables on the IRI of JPCP and CRCP were analysed as well.The results by the comparative analysis showed the prediction accuracy of the IRI of the newly developed MBAS and RF hybrid machine learning model(RF-MBAS)in this study is higher,indicated by the RMSE and R values of 0.2732 and 0.9476 for the JPCP as well as the RMSE and R values of 0.1863 and 0.9182 for the CRCP.The accuracy of this obtained result far exceeds that of the IRI prediction model used in the traditional Mechanistic-Empirical Pavement Design Guide(MEPDG),indicating the great potential of this developed model.The importance analysis showed that the IRI of JPCP and CRCP was proportional to the corresponding input variables in this study,including the total joint faulting cumulated per KM(TFAULT),percent subgrade material passing the 0.075-mm Sieve(P_(200))and pavement surface area with flexible and rigid patching(all Severities)(PATCH)which scored higher.

Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

In this review paper,we present a thorough investigation into the role of pavement technologies in advancing urban sustainability.Our analysis traverses the historical evolution of these technologies,meticulously evaluating their socio-economic and environmental impacts,with a particular emphasis on their role in mitigating the urban heat island effect.The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making(MCDM)framework to choose the optimal pavement application are at the heart of our research.Which serves to assess a spectrum of pavement options,revealing insights into the most effective and sustainable practices.By highlighting both the existing challenges and potential innovative solutions within thefield,this paper aims to offer a directional compass for future urban planning and infrastructural advancements.This review not only synthesizes the current state of knowledge but also aims to chart a course for future exploration,emphasizing the critical need for innovative and environmentally sensitive pavement tech-nologies in the creation of resilient and sustainable urban environments.

Intelligent pavement condition survey:Overview of current researches and practices

Automated pavement condition survey is of critical importance to road network management.There are three primary tasks involved in pavement condition surveys,namely data collection,data processing and condition evaluation.Artificial intelligence(AI)has achieved many breakthroughs in almost every aspect of modern technology over the past decade,and undoubtedly offers a more robust approach to automated pavement condition survey.This article aims to provide a comprehensive review on data collection systems,data processing algorithms and condition evaluation methods proposed between 2010 and 2023 for intelligent pavement condition survey.In particular,the data collection system includes AI-driven hardware devices and automated pavement data collection vehicles.The AI-driven hardware devices including right-of-way(ROW)cameras,ground penetrating radar(GPR)devices,light detection and ranging(LiDAR)devices,and advanced laser imaging systems,etc.These different hardware components can be selectively mounted on a vehicle to simultaneously collect multimedia information about the pavement.In addition,this article pays close attention to the application of artificial intelligence methods in detecting pavement distresses,measuring pavement roughness,identifying pavement rutting,analyzing skid resistance and evaluating structural strength of pavements.Based upon the analysis of a variety of the state-of-the-art artificial intelligence methodologies,remaining challenges and future needs with respect to intelligent pavement condition survey are discussed eventually.

Condition indices for rigid pavements: A comparative analysis of state DOTs using Michigan PMS data

Pavement infrastructure is vital in providing services and links between various sectors of society. Therefore, thepreservation and maintenance of these roads are critical to attaining a pavement network in good conditionthroughout its service life. Various performance indicators like the international roughness index (IRI), pavementcondition index (PCI), and present serviceability rating (PSR) have been used by the state department of transportation (DOT) and highway agencies for evaluating pavement surface conditions and planning future maintenance strategies. Limited data availability, multiple distresses depending on region, lack of correlation of thesecondition indices to maintenance strategies, and data collection limitations pose a challenge for applying theseindices to local conditions. This paper compares condition indices of different states for rigid pavements. Further,using a specific condition index for local conditions is also highlighted. For this purpose, five states and theircorresponding condition indices were evaluated and compared to the Michigan DOT distress index (DI). Thesestates include Virginia, Minnesota, North Dakota, Louisiana, and Oregon. The corresponding distresses of eachcondition index were converted to make them compatible with the MDOT DI. This study used the MDOT'spavement management system (PMS) database to evaluate each condition index for 433 rigid pavement sections.Each distress index was plotted against MDOT DI and compared using a paired t-test. Results show that thecondition indices of Virginia and Minnesota are comparable to DI in terms of the Spearman correlation value. Thet-test results show that except for Virgina, condition indices from other states statistically differ from DI.Therefore, one can't use those directly for local conditions in Michigan. This paper presents the evaluation anddata requirements for each condition index and its impact on selecting a maintenance treatment.

Review on dynamic analysis of road pavements under moving vehicles and plane strain conditions

This paper reviews works on the dynamic analysis of flexible and rigid pavements under moving vehicles on the basis of continuum-based plane strain models and linear theories.The purpose of this review is to provide in-formation about the existing works on the subject,critically discuss them and make suggestions for further research.The reviewed papers are presented on the basis of the various models for pavement-vehicle systems and the various methods for dynamically analyzing these systems.Flexible pavements are modeled by a homogeneous or layered half-plane with isotropic or anisotropic and linear elastic,viscoelastic or poroelastic material behavior.Rigid pavements are modeled by a beam or plate on a homogeneous or layered half-plane with material properties like the ones for flexible pavements.The vehicles are modeled as concentrated or distributed over a finite area loads moving with constant or time dependent speed.The above pavement-vehicle models are dynamically analyzed by analytical,analytical/numerical or purely numerical methods working in the time or frequency domain.Representative examples are presented to illustrate the models and methods of analysis,demonstrate their merits and assess the effects of the various parameters on pavement response.The paper closes with con-clusions and suggestions for further research in the area.The significance of this research effort has to do with the presentation of the existing literature on the subject in a critical and easy to understand way with the aid of representative examples and the identification of new research areas.

Influence of the boundary effect on the mechanical response test of pavement cushion under the wetting effect of silt

Through a self-developed model test system,the mechanical properties of silt and the deformation characteristics of airport runways were investigated during the period of subgrade wetting.Based on the test results,the reliability of the numerical simulation results was verified.Numerical models with different sizes were established.Under the same cushion parameter and loading width ranges,the effects of the cushion parameters and loading conditions on the mechanical responses of the cushion before and after subgrade wetting were analyzed.The results show that the internal friction angles of silt with different wetting degrees are approximately 34°.The cohesion is from 8 to 44 kPa,and the elastic modulus is from 15 to 34 MPa.Before and after subgrade wetting,the variation rates of the cushion horizontal tensile stresses with the same cushion parameters and loading width ranges are different under the influence of boundary effects.After subgrade wetting,the difference in the variation rates of the cushion horizontal tensile stresses under the same cushion parameter range decreases compared with that before subgrade wetting;however,this difference increases under the same loading width range.Before and after subgrade wetting,the influence of the boundary effect on the mechanical response evaluation of the cushion is not beneficial for optimizing the pavement design parameters.When the cushion thickness is more than 0.25 m,the influence of the boundary effect can be disregarded.

Mechanical properties and damage evolution characteristics of waste tire steel fiber-modified cemented paste backfill

During the process of constructional backfill mining,the cemented paste backfill(CPB)typically exhibits a high degree of brittleness and limited resistance to failure.In this study,the mechanical and damage evolution characteristics of waste tire steel fiber(WTSF)-modified CPB were studied through uniaxial compression tests,acoustic emission(AE)tests,and scanning electron microscopy(SEM).The results showed that the uniaxial compressive strength(UCS)decreased when the WTSF content was 0.5%,1%,and 1.5%.When the WTSF content reached 1%,the UCS of the modified CPB exhibited a minimal decrease(0.37 MPa)compared to that without WTSF.When the WTSF content was 0.5%,1%,and 1.5%,peak strain of the WTSF-modified CPB increased by 18%,31.33%,and 81.33%,while the elastic modulus decreased by 21.31%,26.21%,and 45.42%,respectively.The addition of WTSF enhances the activity of AE events in the modified CPB,resulting in a slower progression of the entire failure process.After the failure,the modified CPB retained a certain level of load-bearing capacity.Generally,the failure of the CPB was dominated by tensile cracks.After the addition of WTSF,a gradual increase in the proportion of tensile cracks was observed upon loading the modified CPB sample to the pore compaction stage.The three-dimensional localization of AE events showed that the WTSF-modified CPB underwent progressive damage during the loading,and the samples still showed good integrity after failure.Additionally,the response relationship between energy evolution and damage development of WTSF-modified CPB during uniaxial compression was analyzed,and the damage constitutive model of CPB samples with different WTSF contents was constructed.This study provides a theoretical basis for the enhancement of CPB modified by adding WTSF,serving as a valuable reference for the design of CPB constructional backfill.

Automatic Pavement Crack Detection Based on Octave Convolution Neural Network with Hierarchical Feature Learning

Automatic pavement crack detection plays an important role in ensuring road safety.In images of cracks,information about the cracks can be conveyed through high-frequency and low-fre-quency signals that focus on fine details and global structures,respectively.The output features obtained from different convolutional layers can be combined to represent information about both high-frequency and low-frequency signals.In this paper,we propose an encoder-decoder framework called octave hierarchical network(Octave-H),which is based on the U-Network(U-Net)architec-ture and utilizes an octave convolutional neural network and a hierarchical feature learning module for performing crack detection.The proposed octave convolution is capable of extracting multi-fre-quency feature maps,capturing both fine details and global cracks.We propose a hierarchical feature learning module that merges multi-frequency-scale feature maps with different levels(high and low)of octave convolutional layers.To verify the superiority of the proposed Octave-H,we employed the CrackForest dataset(CFD)and AigleRN databases to evaluate this method.The experimental results demonstrate that Octave-H outperforms other algorithms with satisfactory performance.

Development and Validation of a Scaled Electric Combat Vehicle Tire Model

Pneumatic tire modeling and validation have been the topic of several research papers, however, most of these papers only deal with pneumatic passenger and truck tires. In recent years, wheeled-scaled vehicles have gained lots of attention as a feasible testing platform, nonetheless up to the authors’ knowledge there has been no research regarding the use of scaled tires and their effect on the overall vehicle performance characteristics. This paper presents a novel scaled electric combat vehicle tire model and validation technique. The pro-line lockdown tire size 3.00 × 7.35 is modeled using the Finite Element Analysis (FEA) technique and several materials including layered membrane, beam elements, and Mooney-Rivlin for rubber. The tire-rim assembly is then described, and the rigid body analysis is presented. The tire is then validated using an in-house custom-made static tire testing machine. The tire test rig is made specifically to test the pro-line tire model and is designed and manufactured in the laboratory. The tire is validated using vertical stiffness and footprint tests in the static domain at different operating conditions including several vertical loads. Then the tire is used to perform rolling resistance and steering analysis including the rolling resistance coefficient and the cornering stiffness. The analysis is performed at different operating conditions including longitudinal speeds of 5, 10, and 15 km/h. This tire model will be further used to determine the tractive and braking performance of the tire. Furthermore, the tire test rig will also be modified to perform cornering stiffness tests.

Development and optimization of object detection technology in pavement engineering: A literature review

Due to the rapid advancement of the transportation industry and the continual increase in pavement infrastructure,it is difficult to keep up with the huge road maintenance task by relying only on the traditional manual detection method.Intelligent pavement detection technology with deep learning techniques is available for the research and industry areas by the gradual development of computer vision technology.Due to the different characteristics of pavement distress and the uncertainty of the external environment,this kind of object detection technology for distress classification and location still faces great challenges.This paper discusses the development of object detection technology and analyzes classical convolutional neural network(CNN)architecture.In addition to the one-stage and two-stage object detection frameworks,object detection without anchor frames is introduced,which is divided according to whether the anchor box is used or not.This paper also introduces attention mechanisms based on convolutional neural networks and emphasizes the performance of these mechanisms to further enhance the accuracy of object recognition.Lightweight network architecture is introduced for mobile and industrial deployment.Since stereo cameras and sensors are rapidly developed,a detailed summary of three-dimensional object detection algorithms is also provided.While reviewing the history of the development of object detection,the scope of this review is not only limited to the area of pavement crack detection but also guidance for researchers in related fields is shared.

Flexible pavement longitudinal joint quality evaluation using non-destructive testing

Longitudinal joint construction quality is critical to the life of flexible pavements.Maintaining deteriorated longitudinal joints has become a challenge for many highway agencies.Improving the joint's quality through better compaction during construction can help achieve flexible pavements with longer service lives and less maintenance.Current quality control(QC)and quality assurance(QA)plans provide limited coverage.Consequently,the risk of missing areas with poor joint compaction is significant.A density profiling system(DPS)is a non-destructive alternative to conventional destructive evaluation methods.It can provide quick and continuous real-time coverage of the compaction during construction in dielectrics.The paper presents several case studies comparing various types of longitudinal joints and demonstrating the use of DPS to evaluate the joint's compaction quality.The paper shows that dielectric measurements can provide valuable insight into the ability of various construction techniques to achieve adequate levels of compaction at the longitudinal joint.The paper proposes a dielectric-based longitudinal joint quality index(LJQI)to evaluate the relative compaction of the joint during construction.It also shows that adopting DPS for assessing the compaction of longitudinal joints can minimize the risk of agencies accepting poorly constructed joints,identify locations of poor quality during construction,and achieve better-performing flexible pavements.

Predictive modelling of volumetric and Marshall properties of asphalt mixtures modified with waste tire-derived char:A statistical neural network approach

The goals of this study are to assess the viability of waste tire-derived char(WTDC)as a sustainable,low-cost fine aggregate surrogate material for asphalt mixtures and to develop the statistically coupled neural network(SCNN)model for predicting volumetric and Marshall properties of asphalt mixtures modified with WTDC.The study is based on experimental data acquired from laboratory volumetric and Marshall properties testing on WTDCmodified asphalt mixtures(WTDC-MAM).The input variables comprised waste tire char content and asphalt binder content.The output variables comprised mixture unit weight,total voids,voids filled with asphalt,Marshall stability,and flow.Statistical coupled neural networks were utilized to predict the volumetric and Marshall properties of asphalt mixtures.For predictive modeling,the SCNN model is employed,incorporating a three-layer neural network and preprocessing techniques to enhance accuracy and reliability.The optimal network architecture,using the collected dataset,was a 2:6:5 structure,and the neural network was trained with 60%of the data,whereas the other 20%was used for cross-validation and testing respectively.The network employed a hyperbolic tangent(tanh)activation function and a feed-forward backpropagation.According to the results,the network model could accurately predict the volumetric and Marshall properties.The predicted accuracy of SCNN was found to be as high value>98%and low prediction errors for both volumetric and Marshall properties.This study demonstrates WTDC's potential as a low-cost,sustainable aggregate replacement.The SCNN-based predictive model proves its efficiency and versatility and promotes sustainable practices.

Effect of Seasonal Variations on the Behavior of Flexible Pavements in Burkina Faso: Towards Alternating and Periodic Loading of Multi-Axle Heavy Goods Vehicles for Road Durability

Bituminous materials are heat-sensitive, and their mechanical properties vary with temperature. This variation in properties is not without consequences on the performance of flexible road structures under the repeated passage of multi-axles. This study determines the influence of seasonal variations on the rate of permanent deformation, the rut depth of flexible pavements and the effect of alternating loading of heavy goods vehicles following the temperature variations on the durability of roads. Thus, an ambient and pavement surface temperature measurement was carried out in 2022. The temperature profile at different layers of the modelled pavement, the evaluation of deformation rates and rutting depth were determined using several models. The results show that the permanent deformation and rutting rates are higher at the level of the bituminous concrete layer than at the level of the asphalt gravel layer because the stresses decrease from the surface to the depth of the pavement. On the other hand, the variations in these rates, permanent deformations and ruts between the hot and so-called cold periods are more pronounced in the bitumen gravel than in bituminous concrete, showing that gravel bitumen is more sensitive to temperature variations than bituminous concrete despite its higher rigidity. Of these results, we suggested a periodic and alternating loading of the different types of heavy goods vehicles. These loads consist of fully applying the WAEMU standards with a tolerance of 15% during periods of high and low temperatures. This regulation has increased 2 to 3 times in the durability of roadways depending on the type of heavy goods vehicle.

Design and evaluation of UHPP steel bridge deck pavement for high-temperature and rainy regions

To enhance the serviceability of steel bridge deck pavement(SBDP)in high-temperature and rainy regions,a concept of rigid bottom and flexible top was summarized using engineering practices,which led to the proposal of a three-layer ultra-high-performance pavement(UHPP).The high-temperature rutting resistance and wet-weather skid resistance of UHPP were evaluated through composite structure tests.The internal temperature distribution within the pavement under typical high-temperature conditions was analyzed using a temperature field model.Additionally,a temperature-stress coupling model was employed to investigate the key load positions and stress response characteristics of the UHPP.The results indicate that compared with the traditional guss asphalt+stone mastic asphalt structure,the dynamic stability of the UHPP composite structure can be improved by up to 20.4%.Even under cyclic loading,UHPP still exhibits superior surface skid resistance compared to two traditional SBDPs.The thickness composition of UHPP significantly impacts its rutting resistance and skid resistance.UHPP exhibits relatively low tensile stress but higher shear stress levels,with the highest shear stress occurring between the UHPP and the steel plate.This suggests that the potential risk of damage for UHPP primarily lies within the interlayer of the pavement.Based on engineering examples,introducing interlayer gravel and optimizing the amount of bonding layer are advised to ensure that UHPP possesses sufficient interlayer shear resistance.

Study of the Evolution of Properties of Concrete Containing Used Tire Aggregates

Concrete is generally composed of cement, water, gravel, and sand. However, some research focuses on substituting aggregates with waste materials. In this study, used tires are used as a substitute for gravel. Characteristics such as tensile strength, compressive strength, and porosity were monitored at 7, 14, and 28 days of maturation. The results show that aggregates made from used tires are suitable for concrete production and can replace natural gravel. Regarding the formed concrete, low substitution rates lead to improved concrete properties, but only at an early age. A reaction between the cement and rubber could be the underlying cause. Additionally, the products of this reaction may mitigate the evolution of the compressive strength of the concrete over time.

A systematic review of rigid-flexible composite pavement

Rigid-flexible composite pavement has gained significant popularity in recent decades.This paper provides a comprehensive review of the research progress concerning rigid-flexible composite pavement,aiming to promote its application and address key issues while identifying future directions.The design theory and methodology of rigid-flexible composite pavement are discussed,followed by a description of its structural and mechanical behavior characteristics.The load stress,temperature stress,and their interactive effects between the asphalt layer and the rigid base were analyzed.It is clarified that the asphalt layer serves a dual role as both a“functional layer”and a“structural layer”.Typical distresses of rigid-flexible composite pavement,which primarily occur in the asphalt layer,were discussed.These distresses include reflective cracking,top-down cracking,rutting,and compressive-shear failure.Generally,the integrity of the rigid base and the interlaminar bonding conditions significantly impact the performance and distress of the asphalt layer.The technology for enhancing the performance of rigid-flexible composite pavement is summarized in three aspects:asphalt layer properties,rigid base integrity,and interlaminar bonding condition.The study concludes that developing high-performance pavement materials based on their structural behaviors is an effective approach to improve the performance and durability of rigid-flexible composite pavement.The integrated design of structure and materials represents the future direction of road design.

Loading Stress Analysis of Cement Concrete Pavement in Mountainous Areas

The suitable cement concrete pavement for mountainous areas is a form of low-cost cement concrete pavement that uses unconventional graded stones in different proportions in ordinary concrete,allowing the concrete to fully contact the stones and form a stable and well-bonded slab with large particle stones.As large particle stones replace a certain volume of cement concrete,they have good economic performance and are a low-cost form of cement concrete pavement.This study researches the use of ANSYS tools to analyze the influence of geometric dimensions and material properties of rigid pavement structural layers on the mechanical properties of pavement structures.

Analysis of Historic Pavement and Bridge Conditions and Alternative Funding Levels for the Michigan Department of Transportation

In 1997 the Michigan Department of Transportation (MDOT) established an ambitious set of condition targets for its pavements and bridges, and the Department received increased revenue from a 4-cent-per-gallon increase in the state motor fuels tax to help meet its targets. However, over time, actual revenue was less than both what was initially estimated as needed to meet the targets and what was projected from the tax increase. Consequently, actual conditions were projected to fall short of the target levels, so the department issued bonds to address the shortfall through 2012. To support deliberations on future funding, in 2013 MDOT performed an analysis of historic conditions to determine what additional fuel tax revenues would have been required beginning in 1997 to: replace bond revenues used to fund pavement and bridge projects from 1997 to 2012;and enable MDOT to meet its condition targets. The analysis was performed using data on actual pavement and bridge funding and conditions;as well as predicted funding and conditions for different hypothetical increases in fuel taxes. The analysis concluded that, in addition to the actual increase of 4 cents per gallon, a fuel tax increase of another 10 cents per gallon would have been required in 1997 to replace bond revenue used for pavement and bridges and allow MDOT to meet its condition targets. The analysis results were used to help inform the discussion of Michigan’s target asset conditions and funding, and demonstrate application of MDOT’s pavement and bridge management systems for performing historic analyses.

Study on the Construction Technology of Subgrade Pavement in Road and Bridge Settlement Section

With the continuous development of China’s economy,the construction of roads and bridges work has put forward higher requirements.Due to various factors,the long-term use of roads and bridges will produce a settlement phenomenon.Therefore,it is crucial to address settlement issues during the construction of roads and bridges to ensure that the quality of subgrade and pavement construction meets national regulations.This paper introduces the harm of subgrade pavement subsidence,analyzes the causes of subgrade pavement deformation,and discusses the technical points of subgrade pavement construction,hoping to provide some reference for relevant practitioners.