Pavement Performance Index Research Articles

Optimization and pavement performance of buton-rock-asphalt modified asphalt mixture with basalt-fibre

To optimise the mechanical performance of a buton-rock-asphalt (BRA)- modified asphalt mixture with basalt-fibre (BF), the optimum contents of BF and BRA, as well as the optimal asphalt stone ratio were obtained using response surface methodology (RSM). The feasibility of the mixed-ratio optimised design method was verified via a Marshall stability test. The results indicated that the optimal BF, BRA and asphalt stone ratios were 0.324 %, 22.44 % and 5.23 %, respectively. Moreover, there were some deviations between the average and predicted values of each response index. However, the error range was less than 5 %. A pavement performance index paired comparison matrix calculation method was established, and the pavement performance of the BF-BRA modified asphalt mixture was evaluated using the analytic hierarchy process (AHP). The process comprised eight different content combinations of BF and BRA. The maximum values of dynamic stability, bending strain, immersion Marshall residual stability, and tensile strength ration of BF-BRA modified asphalt mixture were 6512 cycles/mm, 4091 με, 97.4 %, 96.2 % respectively. This indicated that the pavement performance of asphalt mixture can be improved effectively by adding BF and BRA. Additionally, the BF-BRA modified asphalt mixture, which scored highest in pavement performance as evaluated by AHP, aligned with results obtained through response surface methodology(RSM) optimization. This consistency indicates that the BF-BRA modified asphalt mixture derived from RSM exhibits the best pavement performance.

Improved 3D Pavement Texture Reconstruction Method Based on Interference Fringe via Optimizing the Post-Processing Method

The surface quality of pavement has a significant influence on the driving comfort and the skid resistance performance of roads. The 3D pavement texture measurement provides the basis for engineers to calculate the pavement performance index, such as the international roughness index (IRI), the texture depth (TD), and the rutting depth index (RDI), of different types of pavements. The interference-fringe-based texture measurement is widely used because of its high accuracy and high resolution, by which the 3D texture measurement has excellent accuracy in measuring the texture of workpieces with a diameter of <30 mm. When measuring the engineering products with a larger area (or larger areas), such as pavement surfaces, however, the accuracy is deficient because unequal incident angles due to the beam-divergence angle of the laser beam are ignored during the postprocessing of the measured data. This study aims to improve the accuracy of 3D pavement texture reconstruction based on the interference fringe (3D-PTRIF) by considering the influence of the unequal incident angles during postprocessing. It is found that the improved 3D-PTRIF has better accuracy than the traditional 3D-PTRIF, reducing the reconstruction errors between the measured value and the standard value by 74.51%. In addition, it solves the problem of a reconstructed slant surface, which deviates from the horizontal plane of the original surface. Compared to the traditional post-processing method, for the case of smooth surface, the slope can be decreased by 69.00%; for the case of coarse surface, the slope can be decreased by 15.29%. The results of this study will facilitate accurate quantifying of the pavement performance index by using the interference fringe technique, such as IRI, TD, and RDI.

Long-Term In Situ Performance Evaluation of Epoxy Asphalt Concrete for Long-Span Steel Bridge Deck Pavement

Suitable evaluation of distress is beneficial to understanding the in situ performance of deck pavement. This study attempts to evaluate the long-term in situ performance of American ChemCo epoxy asphalt concrete on the Xihoumen Bridge (XHMB) after 12 years of service. The traditional performance indexes were adopted to reveal the performance of XHMB. Then, based on the typical distresses, a new pavement performance index (PPI) was proposed to characterize the authentic distress condition. Finally, the performance evaluation and evolution were conducted. According to the results, the rutting depth indexes and riding quality indexes of all lanes are higher than 97 and 94, respectively. The pavement condition indexes of the pass lanes and drive lanes in 2021 are greater than 94 and 86, respectively, which is contradictory to the distribution of numerous distresses on the pavement. According to the PPI results, the PPIs of the down direction pass lane are mostly 100. However, for the down direction drive lane, the PPIs of about 30% of segments are below 80 or 60. Finally, based on the limited data, the distress of American ChemCo epoxy asphalt concrete may initiate after serving for 4–5 years and then escalate after about 10 years.

Principle analysis of the mix design and performance evaluation of the asphalt-filler volume equivalent substitution method

The asphalt mixture designed with the Marshall mix design method has stable quality and convenient technical management, but the design range of the asphalt-aggregate ratio is small and difficult to adjust, and is therefore difficult to adapt to the design of functional pavement materials with different requirements. In order to solve these problems, the asphalt-filler volume equivalent substitution method (the volume equivalent substitution method) has been proposed. Based on the optimum asphalt-aggregate ratio of the Marshall method, the asphalt-aggregate ratio in the mixture is increased by the equal volume substitution of asphalt and filler. The increase in the asphalt volume is equal to the decrease in the filler volume, and vice versa. With the condition of constant aggregate gradation, the modified asphalt of asphalt mixtures with filler contents of 6.0%, 4.5%, 3.0%, 1.5%, and 0% is designed based on the AC-13 gradation. Based on this, a high-temperature stability test, a low-temperature crack resistance test, a four-point bending fatigue test, and other tests are carried out for the asphalt mixtures. The results show that the dynamic stability of each mix proportion designed with the volume equivalent substitution method is 4924 times/mm even under the most unfavorable conditions (the filler dose is 0%). The maximum bending tensile strain of the specimen with a 0% filler dosage can reach 9667 μ, which is more than twice that of the specimen with a 6% filler dosage. The fatigue test shows that increasing the asphalt content in the mixture is beneficial for improving fatigue durability. The research results show that the material designed by the volume equivalent substitution method has excellent road performance in each proportion. This paper provides a method for the flexible adjustment of the asphalt-aggregate ratio and the asphalt mixture comprehensive road performance. Using this method, the optimum asphalt-aggregate ratio needs to be determined comprehensively according to the stress characteristics and functional requirements of the pavement and the pavement performance index of the mixture, and further research is still needed.

Fuzzy Inference System for Predicting Functional Service Life of Concrete Pavements in Airports

Concerning one of the most important tasks of road structure management is the development of methods to predict their own functional or physical service life, which allows for objectively evaluating the state of road structures that are being considered or are already in operation with minimal labor and monetary incomes. Fuzzy logic systems constitute one successful methodology used for the valuation of pavement degradation. The clustering that focuses on pavement degradation conditions is normally performed by a visual inspection or using data collected by automated distress measurement equipment. Fuzzy sets theory provides different advantages for including a certain degree of uncertainty in the pavement performance index, subjective analysis, and maintenance assessments and can greatly improve consistency and reduce subjectivity in the degradation process. The main objective of this study was to develop a new fuzzy logic-based model to predict the functional service life of concrete pavement conditions and maintenance action evaluations concerning the airport network of Viña del Mar, Central Chile, and using pavement distress data from the Directorate of Airports, Ministry of Public Works of Chile. The proposed fuzzy logic model can be remarkably beneficial for design, construction, and maintenance, to evaluate design decisions for the measurable and objective valuation of deviations in the quality of construction, and for timely forecasting work based on continuous observing of the current infrastructure system.

Optimisation method of network level pavement maintenance planning based on benefit maximisation subject to budget constraints and a case study

ABSTRACT Considering that the decision-making and planning of large-scale highway network under the condition of limited funds, there are some problems such as complex algorithm of feasible solution of maintenance scheme and low efficiency of optimisation process, a heuristic maintenance planning optimisation algorithm based on budget is introduced. This paper focuses on the performance prediction, the determination of treatment measures and the optimisation of the optimal scheme. Firstly, through the analysis of the technical process of prediction and treatment measures, the pavement performance degradation models of pavement condition index, riding quality index and rut depth index based on treatment level are established. Then, based on the characteristics of pavement performance degradation in China, the concept of maintenance benefit based on pavement performance index is proposed, and the cost-benefit optimisation model of highway asphalt pavement is established. A budget-based heuristic algorithm is proposed to solve the optimisation model for maintenance planning with budget constraints. Finally, taking Lian-Xu highway network in a case study, the optimal scheme of treatment measures and fund allocation for the maintenance section of the large-scale highway network is realised under the condition of limited funds, so as to verify the feasibility of the optimisation model.

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

Prediction method of pavement performance based on same dimension gray recurrence dynamic model

In order to accurately grasp the change trend of asphalt pavement performance index, taking the rutting depth index (RDI) as an example, we establish a gray recurrence dynamic model with equivalent dimension which can use the new data effectively and dynamically. The model is used to predict the indexes such as pavement condition index (PCI), driving quality index (RQI) and skidding resistance index (SRI). The results show that in step 3, the minimum error probabilities of RDI, PCI, RQI and SRI are all 1, and the posterior prescription variance ratios are: 0.111 7, 1, 0.065 4, 1, 0.201 8, and 0.113 0, respectively. It is proved that with the increase of recursive steps, the accuracy of the prediction result of the model becomes higher, and the error becomes less, which shows that the method can accurately predict the road performance.

International roughness index prediction based on multigranularity fuzzy time series and particle swarm optimization

The effective prediction of pavement performance trends can help in achieving the cost-effective management of pavements over their service life. The international roughness index (IRI) is a widely used pavement performance index, which can be considered as a time-dependent variable in terms of scientific modeling. This research aims to develop an innovative IRI prediction model based on fuzzy-trend time-series forecasting and particle swarm optimization (PSO) techniques. Raw datasets extracted from the Long-Term Pavement Performance database are used for model training, testing, and performance assessment. First, IRI values are divided into different granular spaces, which are considered as the principal factor and subfactors. In addition, the multifactor interval division method is proposed according to the principle of the automatic clustering technique. Next, a second-order fuzzy-trend model and fuzzy-trend relationship classification method are proposed to predict the fuzzy-trend of each factor. Then, the fuzzy-trend states for multiple granular spaces are generated while giving full consideration to various uncertainties. Finally, the PSO technique is used to optimize the performance model while carrying out future IRI forecasting. Comparative experiments are performed using more than 20,000 data items from different regions to verify the effectiveness of the proposed method. The experimental results indicate that the proposed method outperforms other approaches including the polynomial fitting, autoregressive integrated moving average, and backpropagation neural network methods in terms of the root mean squared error (0.191) and relative error (6.37%).

Influence of angularity and roughness of coarse aggregates on asphalt mixture performance

The damage of asphalt mixture occurs in asphalt-aggregate interphase. The strength was directly associated with the overall performance of mixture. In this paper, Marshall test was applied to investigate the high-temperature stability. The high-temperature stability, water stability and low-temperature performance of five types of asphalt mixtures were tested through Marshall test, and the correlation between road performance dynamic stability, freeze-thaw split strength ratio, and low-temperature flexural tensile strength and average angular coefficient of coarse aggregate was studied. Moreover, the correlations of asphalt-aggregate interphase strength to the pavement performance index of asphalt mixture were also established.

Analysis of Design Index and Mechanical of Asphalt Pavement Structure in the Northwest Desert Areas

In this paper, pavement performance index PCI, road surface deflection and pavement rutting are proposed as the design indexes of pavement structure by analyzing the desert region of bad natural environment under heavy load traffic asphalt pavement condition and using finite element analysis. The stress distribution of durable asphalt pavement structure in desert area was obtained. The results showed that it is an approximate linear relationship between maximum vertical deformation of road surface and wheel load under different wheel load. With the increase of axial load, the maximum vertical deformation increases gradually. The maximum tensile stress of the road surface is symmetrical distribution with the wheel axis. The shear stress in the pavement structure increases with the increase of depth, and the shear stress reaches the peak value in the distance from the road surface 5cm. The results of the research can be a scientific theoretical support and a technical guidance for the selection and structural design of the asphalt pavement in the desert region.

Pavement Performance Index for Indian rural roads

Summary The performance of a road is evaluated from time to time so as to improve its quality and helps in planning maintenance of roads. For this purpose various pavement deteriorating models as a decision tool are available. But they are not easy to use for field engineers due to either huge past data requirement or complicated calculations. Therefore, this paper presents a Pavement Performance Index for rural roads by using simple methodology. The distress parameters of rural roads were identified through literature review. Similarly rating criteria for each distress parameters were identified through literature. For final selection of distress parameters in context of Indian rural road, opinions of five highly experienced industrial experts were taken. After that the weightage for severity of each parameter causing distress of pavement is calculated by using data of questionnaire survey in which 117 professionals working in Pradhan Mantri Gram Sadak Yojana across the country were participated. The paper suggests a formula to decide Pavement Performance Index that depends on rating criterion and severity weightage of distress parameters of pavement performance. The study concluded that suggested Pavement Performance Index makes calculations easy for field engineers and will be useful to decide priority list of rural roads for repair and maintenance schedule.

Prediction of Pavement Performance: Application of Support Vector Regression with Different Kernels

The pavement performance model is a basic part of the pavement management system. The prediction accuracy of the model depends on the number of effective variables and the type of mathematical method that is used for modeling the pavement performance. In this paper, the capability of the support vector machine (SVM) method is analyzed for predicting the future of the pavement condition. Five kernel types of SVM algorithm are formed and nine input variables of the proposed models are extracted from the range of effective variables on the pavement condition. The international roughness index is used as the pavement performance index. The results show that the Pearson VII Universal kernel can accurately predict pavement performance in its life cycle.

Analysing the accuracy of pavement performance models in the short and long terms: GMDH and ANFIS methods

The accuracy of pavement performance prediction is a critical part of pavement management and directly influences maintenance and rehabilitation strategies. Many models with various specifications have been proposed by researchers and used by agencies. This study presents nine variables affecting pavement condition and analyses the accuracy of the Group Method of Data Handling (GMDH) and Adaptive Neuro Fuzzy Inference System (ANFIS) models in predicting pavement performance in short and long terms of a pavement life cycle. The nine effective variables are extracted from groups of pavement age, traffic conditions, environmental changes and pavement structure. The International Roughness Index (IRI) is used as the pavement performance index. Results show that GMDH with 1st, 2nd, 3rd and 4th-order polynomials is not able to predict pavement performance for short and long terms. However, the specified ANFIS models can accurately predict pavement performance in the short term, but not in the long term.

Strategic Total Highway Asset Management Integration

To manage a significant quantity of aging roadway infrastructure and growing traffic volume successfully, agencies are faced with challenges in developing reliable long-term plans that maximize network performance by optimizing programming preservation projects at the network level. Current practice typically involves relatively independent planning for bridge and pavement subassets, with a slight number of situations allowing for reliable trade-off analysis between the two. The choice to improve two bridges rather than one pavement section may yield a greater percentage increase in the bridge network performance than one pavement section would for the pavement network performance. The reliability of this choice being right and at the right time significantly decreases over the long term. Mutually inclusive highway asset planning by an integration of the bridge subasset into pavement subasset significantly increases long-term planning reliability. A key point of this strategic total highway asset management integration (STHAMi) approach is the conceptual structural integration factor. Integrating the bridge condition index into a pavement performance index allows for the treatment of bridges as equivalent pavement sections. STHAMi resulted in a higher percentage of model network treated per unit of value, coupled with consistently higher annual network performance during a 25-year span. Key benefits include the introduction of one pavement performance indicator as an overall encompassing highway performance measure for combined long-term bridge and pavement subasset planning. The approach makes long-term planning for both subassets possible in a pavement-oriented engineering organizational unit.

A Study on the Test of Rubber Crumb Modified Asphalt Mixture Road Performance

The article is based on the rubber crumb modified asphalt’s fundamental characteristics, paving a test road. Through test and compacted study of indoor pavement performance and technical index on-site, summarizing relevant experience, providing reference for similar engineering application