Total Pavement Research Articles

A Comparative Study of Pavement Roughness Prediction Models under Different Climatic Conditions

Predicting the International Roughness Index (IRI) is crucial for maintaining road quality and ensuring the safety and comfort of road users. Accurate IRI predictions help in the timely identification of road sections that require maintenance, thus preventing further deterioration and reducing overall maintenance costs. This study aims to develop robust predictive models for the IRI using advanced machine learning techniques across different climatic conditions. Data were sourced from the Ministry of Energy and Infrastructure in the UAE for localized conditions coupled with the Long-Term Pavement Performance (LTPP) database for comparison and validation purposes. This study evaluates several machine learning models, including regression trees, support vector machines (SVMs), ensemble trees, Gaussian process regression (GPR), artificial neural networks (ANNs), and kernel-based methods. Among the models tested, GPR, particularly with rational quadratic specifications, consistently demonstrated superior performance with the lowest Root Mean Square Error (RMSE) and highest R-squared values across all datasets. Sensitivity analysis identified age, total pavement thickness, precipitation, temperature, and Annual Average Daily Truck Traffic (AADTT) as key factors influencing the IRI. The results indicate that pavement age and higher traffic loads significantly increase roughness, while thicker pavements contribute to smoother surfaces. Climatic factors such as temperature and precipitation showed varying impacts depending on the regional conditions. The developed models provide a powerful tool for predicting pavement roughness, enabling more accurate maintenance planning and resource allocation. The findings highlight the necessity of tailoring pavement management practices to specific environmental and traffic conditions to enhance road quality and longevity. This research offers a comprehensive framework for understanding and predicting pavement performance, with implications for infrastructure management both locally and worldwide.

Statistical and machine learning models for predicting spalling in CRCP

Continuously reinforced concrete pavement (CRCP), crucial for the resilience of transportation infrastructure owing to its continuous steel reinforcement, confronts a critical challenge in the form of spalling—a distress phenomenon posing a threat to pavement durability and overall structural integrity. The detachment or breakage of concrete from the surface compromises CRCP’s functionality and raises safety concerns and escalating maintenance costs. To address this pressing issue, our study investigates the multifaceted factors influencing spalling, employing a comprehensive approach that integrates statistical and machine learning techniques for predictive modeling. Descriptive statistics meticulously profile the dataset, emphasizing age, thickness, precipitation, temperature, and traffic parameters. Regression analysis unveils key relationships, emphasizing the significance of age, annual temperature, annual precipitation, maximum humidity, and the initial International Roughness Index (IRI) as influential factors. The correlation matrix heatmap guides feature selection, elucidating intricate interdependencies. Simultaneously, feature importance analysis identifies age, Average Annual Daily Traffic (AADT), and total pavement thickness as crucial contributors to spalling. In machine learning, adopting models, including Gaussian Process Regression and ensemble tree models, is grounded in their diverse capabilities and suitability for the complex task at hand. Their varying predictive accuracies underscore the importance of judicious model selection. This research advances pavement engineering practices by offering nuanced insights into factors influencing spalling in CRCP, refining our understanding of spalling influences. Consequently, the study not only opens avenues for developing improved predictive methodologies but also enhances the durability of CRCP infrastructure, addressing broader implications for informed decision-making in transportation infrastructure management. The selection of Gaussian Process Regression and ensemble tree models stems from their adaptability to capture intricate relationships within the dataset, and their comparative performance provides valuable insights into the diverse predictive capabilities of these models in the context of CRCP spalling.

Fuzzy Rule Based System of Optimal Pavement Maintenance and Rehabilitation Strategies for Yangon-Mandalay Expressway

Purpose: Systematic pavement management plays a vital role in the better Road Asset Management system. The lifespan of pavement can be preserved and prolonged by adequate maintenance measures in proper time. By early detection and repair of defects at initial stages with predictive maintenance reduces the rapid deterioration of the pavement. Moreover, inaccuracy in pavement deterioration prediction leads to an improper maintenance with wastage of time, cost and labor strength. To overcome all of these obstacles, this paper attempts an approach on optimal pavement maintenance strategy by means of fuzzy rule-based system. Materials and Methods: In this research, four pavement indicators of PCI, IRI, PSR and PSI have been taken into account as antecedents and five different types of pavement maintenance as consequents. In this research, ASTM D-6433, Road Lab Pro software, AASHTO guidelines and Fuzzy Logic (Mamdani) model have been used to evaluate the current pavement condition and optimal pavement maintenance strategies. Findings: According to research area, 130 total pavement sample units were undertaken to study for the mean pavement condition of PCI value 54.93 (poor), IRI 7.01 (fair), PSR 3.33 (fair) and PSI 3.35 (fair). Due to 13 years-old life span of traffic volume, temperature and other external factors, this expressway is suffering from potholes, bleeding, longitudinal and transverse cracking, weathering, joint reflection cracking for Asphalt Concrete (AC) overlay and linear cracking, joint seal failure, scaling, faulting, depression, lane/shoulder drop off for existing concrete pavement. According to the fuzzy logic model results, 42 numbers of fuzzy If-Then maintenance rules were verified as the most relevant pavement maintenance and rehabilitation strategies for Yangon-Mandalay Expressway. Implications to Theory, Practice and Policy: This research provide implications to the study and contributions to theory, practice and policy. This research paper insights into effective infrastructure maintenance and investment, emphasizing the role of advanced computational techniques in transportation economics. The key advantage of this research paper is to be effective, supportive, easy and accessible decision-making tool for transportation and pavement engineers, expressway planners and highways department authorities especially from developing countries.

Cost Comparison of Flexible Pavement on Weak Sub-Grade Soil Modified with Lime and SD

The effectiveness of flexible pavement is affected by the subgrade quality. The subgrade refers to a compacted layer of soil that provides sideways support to the pavement. When constructed on a weak subgrade, it negatively impacts the pavement's performance, leading to a shorter lifespan. Traditionally, the common method to stabilize a soft subgrade involves removing the weak soil and replacing it with stronger soil. However, due to the high expenses associated with soil replacement, highway agencies are exploring alternative approaches to constructing highways on soft subgrades. Soil stabilization is a commonly employed alternative in pavement construction, serving as an effective method to enhance the engineering characteristics of soil, including its strength and stability. This paper focuses on the utilization of lime and stone dust (SD) as admixtures for an efficient ground improvement technique over weak subgrade soil deposits. The California Bearing Ratio (CBR) test is conducted by making the specimens of weak subgrade by adding the variable percentages of a mixture of lime and SD. First, the soil was mixed up with lime to 12% by weight with an increment of 3% again the soil was mixed with SD with increments of 10% up to 50% by weight of soil. The study determined an optimal lime content of 3% based on the geotechnical properties of the mixture and the cost considerations of lime and the weak subgrade. Following this, SD was added to the optimized lime-weak subgrade mixture in varying increments of 10% by weight, up to a maximum of 40%. The modified mixes were then evaluated for their CBR and maximum dry density values. The CBR is increased to 15% and the total pavement thickness decreased to 725 mm for 50% SD addition with 4.89 % in cost reduction.

ANALISA PERENCANAAN RUNWAY 10 TAHUN KEDEPAN DI BANDARA NGLORAM KABUPATEN BLORA JAWA TENGAH

Abstract
 Ngloram Airport – Blora is an airport located 40 km from the center of Blora city which is managed by the Ministry of Transportation after being donated by the Ministry of Energy and Mineral Resources. At the time of writing, Ngloram – Blora Airport still has the status of a Service Unit under the Airport Management Unit. The existing condition of this airport is that it has a runway with dimensions of 1500 m x 30 m and the most critical aircraft is the ATR 72-600. It is stated in KM 231 of 2019 concerning Determining the Location of Ngloram Airport that the critical aircraft listed in the phase III development plan are new, larger critical aircraft that are planned for operation. Given this, in order for this type of aircraft to operate optimally, it requires extending and widening the runway. The aim of this research is to determine the actual need for runway length in accordance with the Airplane Reference Field Length (ARFL) and runway width in accordance with the type of aircraft planned to operate, and also to know the sufficient thickness of pavement along with the budget ceiling required for the work. -the job in question.
 Based on the results of the analysis that has been carried out, the dimensions of the extension are 1000 meters with a width of 45 meters and the widening of the existing runway is 15 meters with a total pavement thickness of 82.5 cm. With the thick pavement construction as stated, a PCN value of 50 F/C/X/T was obtained from the calculation of the FAARFIELD 1.42 software application and the budget ceiling required for these works was Rp. 73,663,700,000.00
 Keywords: Runway, runway l
 Abstract
 Ngloram Airport – Blora is an airport located 40 km from the center of Blora city which is managed by the Ministry of Transportation after being donated by the Ministry of Energy and Mineral Resources. At the time of writing, Ngloram – Blora Airport still has the status of a Service Unit under the Airport Management Unit. The existing condition of this airport is that it has a runway with dimensions of 1500 m x 30 m and the most critical aircraft is the ATR 72-600. It is stated in KM 231 of 2019 concerning Determining the Location of Ngloram Airport that the critical aircraft listed in the phase III development plan are new, larger critical aircraft that are planned for operation. Given this, in order for this type of aircraft to operate optimally, it requires extending and widening the runway. The aim of this research is to determine the actual need for runway length in accordance with the Airplane Reference Field Length (ARFL) and runway width in accordance with the type of aircraft planned to operate, and also to know the sufficient thickness of pavement along with the budget ceiling required for the work. -the job in question.
 Based on the results of the analysis that has been carried out, the dimensions of the extension are 1000 meters with a width of 45 meters and the widening of the existing runway is 15 meters with a total pavement thickness of 82.5 cm. With the thick pavement construction as stated, a PCN value of 50 F/C/X/T was obtained from the calculation of the FAARFIELD 1.42 software application and the budget ceiling required for these works was Rp. 73,663,700,000.00
 Keywords: Runway, runway length and width, own estimated price, FAARFIELD 1.42.

Expansion method and application of initial deflection data for asphalt pavement based on the unascertained number theory: a case study

Deflection is an essential parameter for pavement structural condition assessment. For the total pavement section length, sample size for deflection data is relatively small, which makes it challenging to characterize the pavement structural properties. To solve the problem, an expansion method for the initial deflection data based on unascertained number theory was proposed in this study. And the decay evaluation of the pavement structure strength during service was conducted based on pavement deflection samples before and after expansion. Results showed that after expansion, deflection sample size increases exponentially and the deflection range was broadened significantly. And the decay analysis of the pavement structure strength ratios at two – and three-years demonstrated that the expanded deflection sample can lead to a more reasonable evaluation of the initial pavement structural performance. The study can help to understand the decay laws of the pavement structure performance to make pavement maintenance plans more rationally.

PLANNING OF FLEXIBLE PAVEMENT THICKNESS FOR NEW RUNWAY IN SUPADIO INTERNATIONAL AIRPORT WITH FEDERAL AVIATION ADMINISTRATION METHOD

The runway is one component in the airport system, its performance greatly affectsall airport operational activities. Anticipating the increase in services from thecapacity of the number of passengers, it is necessary to build a new runway. In thisstudy, analyze the forecast of the number of movements with the trend analysismethod and the percent forecast method from PT. Angkasa Pura II, field subgradeCBR, new runway capacity and planning year, and new runway pavement using theFederal Aviation Administration (FAA) method and FAARFIELD 1.42 software.Based on the analysis results, the field subgrade CBR was 0.38% < 3%, then it wasstabilized using selected soil (CBR 20.523%) with a thickness of 60 cm. The forecastresults with both methods show that the trend analysis method is used because thetime is earlier than other methods, namely in 2027 with the existing runway capacityat Supadio International Airport of 54 operations/hour with a maximum capacity of51 operations/hour. The results of the runway flexible pavement thickness using theFAA method manually obtained a total pavement thickness of 42” (107 cm), whichconsists of 4”(10 cm) Surface Course, 12”(31 cm) Base Course, and 26”(66 cm)Subbase Course, while the FAARFIELD 1.42 software has a total pavementthickness of 30.43”(77 cm), which consists of 4”(10 cm) Surface Course, 5” (13 cm)Base Course, and 21.43”(54 cm) Subbase Courses.

PLANNING OF FLEXIBLE PAVEMENT THICKNESS FOR NEW RUNWAY IN SUPADIO INTERNATIONAL AIRPORT WITH FEDERAL AVIATION ADMINISTRATION METHOD

The runway is one component in the airport system, its performance greatly affectsall airport operational activities. Anticipating the increase in services from thecapacity of the number of passengers, it is necessary to build a new runway. In thisstudy, analyze the forecast of the number of movements with the trend analysismethod and the percent forecast method from PT. Angkasa Pura II, field subgradeCBR, new runway capacity and planning year, and new runway pavement using theFederal Aviation Administration (FAA) method and FAARFIELD 1.42 software.Based on the analysis results, the field subgrade CBR was 0.38% < 3%, then it wasstabilized using selected soil (CBR 20.523%) with a thickness of 60 cm. The forecastresults with both methods show that the trend analysis method is used because thetime is earlier than other methods, namely in 2027 with the existing runway capacityat Supadio International Airport of 54 operations/hour with a maximum capacity of51 operations/hour. The results of the runway flexible pavement thickness using theFAA method manually obtained a total pavement thickness of 42” (107 cm), whichconsists of 4”(10 cm) Surface Course, 12”(31 cm) Base Course, and 26”(66 cm)Subbase Course, while the FAARFIELD 1.42 software has a total pavementthickness of 30.43”(77 cm), which consists of 4”(10 cm) Surface Course, 5” (13 cm)Base Course, and 21.43”(54 cm) Subbase Courses.

Development of a Road Pavement Structure Diagnostic Procedure Based on the Virtual Inertial Point Method

Falling weight deflectometers (FWD) are utilised worldwide to analyse the condition and the load-bearing capacity of road pavement structures. One of the FWD measurement results, the deflection bowl, may provide surplus information that is suitable for better road pavement structure diagnostics, based on the novel approach presented in this paper. This study presents a computational method that can calculate the layer thicknesses from the deflection data recorded by the non-destructive FWD device. The motivation for this research is that FWD and GPR equipment are often not available at the same time. However, the back-calculation of the pavement layer moduli from the deflections requires knowledge of the exact thicknesses. The developed method is based on the inertia point principle and provides not only the total pavement thickness but also the total asphalt thickness at each FWD drop point. From 25,200 linear elastic layered pavement models, 350 virtual inertia points could be identified. To describe the relationship between the structural model characteristics of the pavement (thickness and subgrade modulus) and the virtual inertia points, we chose the Gaussian process regression, a widely used method in machine learning. In addition to the thicknesses, the point of inertia can also be used to calculate the bearing modulus of the subgrade with high accuracy. Based on the data from the experimental road section, the radius value of the inertia point rc is not sensitive to the stiffness of the layers that compose the pavement structure, depending only on the total pavement thickness and the bearing capacity of the subgrade. The calculation was compared with the AASHTO (1993) procedure, and very similar values for the subgrade-bearing capacity were obtained. Moreover, in the near future, the method can be further developed to provide an estimation of layer thicknesses, together with a deflection measurement, especially adapted to continuous deflection measurement devices (Curviameter and Rolling Wheel Deflectometer).

Improved Multi-layer Analysis of Pavement Response Using Neural Networks to Optimize Numerical Integration

This paper presents a new accurate method to compute the mechanical response of pavement structures using an Artificial Neural Network (ANN) model coupled with Multi-Layer Elastic Analysis (MLEA). The ANN model is used to improve the numerical integration of the response function used in the MLEA method. It requires four inputs: total pavement thickness, the diameter of the contact area, radial distance, and depth of the response point; and it was trained on one million hypothetical pavement structures. The developed method has been validated by a comparative analysis against boundary conditions, finite element analysis, and available MLEA solutions using various hypothetical pavement structures. The results demonstrate that the developed solution gives excellent response in the vicinity of the pavement surface together with a significant improvement in computational efficiency.

Thickness and Cost Comparison of Cement Treated and Granular Base for Flexible Pavement: A Case Study of Pathlaiya-Nijgadh Section of East-West Highway of Nepal

A pavement is considered a multi-layer system that distributes the vehicular load over a large area and transfers it to the foundation. Flexible pavement is mainly deteriorated due to the failure of its layer as well as the subgrade soil. Resisting the vehicular load requires the appropriate thickness of the sub-base and base with optimization of cost. This study aims to find the effect of the cement-treated base on thickness, unit cost, and life cycle cost. Design traffic was estimated for 15 years design period with an annual traffic growth rate of 5% for the Pathlaiya-Nijgadh Section of the East-West Highway of Nepal. The thickness of the granular base and the cement-treated base was 500 mm and 357.43 mm for design traffic of 34.86 million standard axles (msa) and the total pavement thickness for design traffic of 34.86 msa was 590 mm and 457.43 mm respectively. The comparison of cost estimates for the base course revealed that there was a 5.63% reduction in the per km cost of the cement-treated base as compared to the granular base. The cement-treated base seems to be a viable alternative to the base course for road construction as compared to the granular base. The pavement maintenance using a Cement-Treated Base (CTB) was 47.31% more economical than pavement maintenance using a granular base course. The total cost including initial investment and the cost of the maintenance of the pavement construction using CTB was 24.39% lower than that of the granular base.

Risk-based pavement maintenance planning considering budget and pavement deterioration uncertainty

Although some parameters are uncertain in pavement Maintenance and Rehabilitation (M&R) planning, most of the literature has considered these parameters deterministic. Likewise, minimizing risk has been an immense concern as a significant amount of money should be spent on the M&R of pavement networks. To this end, this study aims to propose a new approach to consider risk and uncertainty in a pavement M&R optimization problem. A Multistage Stochastic Integer Programming including risk constraints is applied for the problem modeling. Conditional Value at Risk index is applied to minimize the mentioned variables and avoid unacceptable risks. Subsequently, a case study is used to analyze the proposed technique’s effectiveness. The results indicate that the total pavement M&R agency cost equals 6.33 billion Tomans considering a confidence level of 95%. Furthermore, the proposed approach can detect the optimal value of the annual budget for pavement network M&R, which is 1.96 billion Tomans for the case study. Applying preventive maintenance can compensate for the negative effects of risk on projects. Therefore, the proposed approach can help decision-makers, policymakers, and transport agencies to analyze and control risk in the pavement M&R optimization problems and determine the optimal M&R budget.

Sustainable Adaptive Cycle Pavements Using Composite Foam Concrete at High Altitudes in Central Europe

Climate pavement adaptability is an integral part of a holistic concept of road design, construction, and pavement management. One of the possibilities for fulfilling the mentioned author’s premise in sustainable cycle pavements in the cold region of Central Europe is using composite foam concrete (CFC). To establish the credibility of the design of these pavements, we objectified the correlation dependencies of average annual air temperatures and frost indexes, for altitude regions from 314 to 858 m in the period 1971 to 2020, at its height above sea level. As part of the research on the increase in tensile strength during bending of CFC, extensive laboratory measurements were carried out and validated by isomorphic models of real roads, which enabled an increase in tensile strength during bending from 0.376 to 1.370 N·mm−2 for basalt reinforcing mesh. The research results, verified through FEM (Finite Element Method) models of cycle pavements, demonstrated a possible reduction of total pavement thickness from 56 to 38 cm for rigid pavements and 48 to 38 cm for flexible pavements.

Potential Investigation of Stabilised Fuming Furnace Slag for Road Construction

Fuming furnace (FF) slag is one of the industrial waste materials which is generated during extraction of zinc metal at the zinc industry. It is deposited at the designated FF slag yard near the plant area with very limited use. As a result, the deposits are increasing year after year posing threat to the environment and occupying large area of precious land. The present research explores the possibility of using this waste material in the road construction. The tests like Scanning electron microscope (SEM), Energy dispersive spectrometer (EDS) and X-ray diffraction was carried out on FF slag. To improve its geotechnical properties, it was mechanically stabilised with jarofix (another waste material generated from the same zinc industry) in the range of 25 to 75 percent. Apart from compaction characteristics, shear strength and consolidation characteristics of these mixes were studied to conclude about its feasibility in embankment and granular layers of road pavement. These mixes were further chemically stabilized with cement in the range of 3 to 9 percent to investigate their potential application in sub base and base layers of road construction. Compressive and durability characteristics of these mixes were also studied. Detailed laboratory study concluded that FF slag is a porous; amorphous cohesionless coarse grained material with high angle of internal friction. Engineering properties viz. dry density, CBR, and shear strength characteristics improved significantly after mechanical stabilisation with jarofix. These parameters of FF slag were compared with other industrial waste materials. Unconfined compressive strength and durability characteristics indicated suitability of cement stabilised slag-jarofix mixes for sub base and base layers of road pavement. It was concluded that about 20-30 percent of FF slag can be used as a replacement of fine aggregate in these granular layers. A typical pavement design indicated that it is possible to reduce the total pavement thickness of about 13 percent by using cement stabilised slag-jarofix mix.

Concrete Modular Pavement Structures with Optimized Thickness Based on Characteristics of High Performance Concrete Mixtures with Fibers and Silica Fume.

Usually, C30/37 strength class concrete is used to construct concrete pavements on a rigid, semi-rigid or flexible base. Concrete with such a strength delivers essential design characteristics: flexural strength and tensile splitting strength are between 4.5–5.4 MPa and 2.8–3.7 MPa, respectively. Design characteristics can be significantly increased by densifying the concrete mixture, i.e., adding silica fume, steel or polypropylene macro fibers. As high-performance concrete characteristics are 20–60% higher than those for standard concrete (C30/37), new possibilities to reduce the thickness of concrete pavement slabs appear. The theoretical analysis of concrete pavement structures with high-performance concrete mixtures (C40/50, C45/55 and C50/60) showed that slab thickness could be reduced by 6–39% compared to a standard concrete pavement structure depending on the concrete properties and design method. From all those pavement structures, three concrete mixtures were determined as the most rational ones in terms of PCP thickness reduction and total pavement cost: (i) with 49.5 kg/m3 of steel fibers and 25.2 kg/m3 of silica fume; (ii) with 10.0 kg/m3 of polypropylene fibers (type A); (iii) with 49.5 kg/m3 of steel fibers.

Pavement damage costs by truck class and economy of scale relative to increased loading

ABSTRACT This research quantified the impact that truck mix, distress severity, and climate have on pavement damage and maintenance costs based on Long-Term Pavement Performance (LTPP) sections. Cost analysis was conducted using in-situ records of maintenance and rehabilitation data from 1988 to 2016. The paper quantified damage cost per VMT and ESAL-mile for each FHWA truck class. Economies of scale are evident in the cost per ESAL-mile relative to total pavement loading as segments carrying higher traffic loads require additional maintenance and rehabilitation, however additional cost for these procedures is outpaced by the increase in traffic resulting in a reduction in the pavement damage cost per ESAL-mile. The cost per ESAL-mile varied from $0.01 to $0.37 per ESAL-mile depending on total loading, a relationship that is accurately modeled (R 2 = 0.97) using the developed power function. Results also show that vehicle class, and thereby the number and distribution of ESALs, significantly impacts the pavement damage cost. The research developed an accurate and robust model correlating pavement damage cost per ESAL-mile to the accumulated number of ESALs during the pavement service life. Transportation agencies can utilize this model to determine a fair variable compensation for the pavement damage imposed by individual trucks.

Effect of reclaimed asphalt pavement in granular base layers on predicted pavement performance in Egypt

This research presents the prediction of pavement performance constructed with base layer consisting of reclaimed asphalt pavement (RAP)/virgin aggregate blends. The prediction was made by the Multi-Layer Elastic Analysis software (KENLAYER) in terms of horizontal tensile strain at the bottom of AC layer and the vertical resilient strain at critical locations within the pavement system. The dynamic modulus |E*| for the hot mix asphalt was estimated by using the quality-related specifications software considering three different climatic conditions and two levels of design speeds. Finally, total pavement rutting and fatigue cracking were determined using the critical strains computed by the Multi-Layer Elastic Analysis along with the Mechanistic Empirical Pavement Design Guide performance models and transfer functions. In general, the RAP blends showed superior/comparable performance compared to natural aggregates for the application in base/subbase layers for the Egyptian conditions. The effect of the rate of loading and climate conditions was significant on both asphalt concrete layer fatigue cracking and rutting.

Local Versus Full Width Pavement Rehabilitation in the Frame of Old Water Supply Network Repair

Since the global financial crisis of 2008, all construction related activities are now subject to cost control of each project. An important component of the optimal choice is the implementation cost. The evaluation of construction activities can be conducted by estimating their environmental as well as their cost footprint, which is also the demand and consumption measure for the societies' needs. Water and sewerage projects have a key role in the standard of living, Public Health and environment. Therefore, water supply network replacements are important to upgrade the quality and quantity of water, through cost-effective choices. The purpose of this study is to present and comment on the uniform cost footprint through the complete replacement of the old water supply network along with complete reconstruction of pavement compared to local repair activities. Usual practices in repair works of old networks and flexible pavement rehabilitations are presented, assessing the benefits of total reconstruction by carrying out life cycle cost analysis in terms of uniform cost per year. The project of replacing the water supply network in the municipality of Larissa, Greece for the period 2015-2019 is analyzed, linking water savings with simultaneous total pavement rehabilitation, calculating average cost per inhabitant and hydrometer, comparing cost and pavement surface area between total and localized rehabilitation activities for a twenty-year rollback period. The fruitful findings of this research study, indicate that full-width pavement rehabilitation along with new water supply network establishment is economically advantageous compared to local rehabilitation treatments, according to the time period considered. Thus, competent authorities can use the proposed methodology as a useful tool to conclude to the optimal choice for maintaining water supply networks in a cost-effective way.

Multi-input performance prediction models for flexible pavements using LTPP database

Pavement performance prediction is a primary concern for pavement researchers and practitioners. The impact of climatic conditions and traffic characteristics on pavement performance is indisputable. The main objective of this study is to investigate the combined effect of both climate and traffic loading on pavement performance. Multi-input performance prediction models in terms of the well-known Pavement Condition Index (PCI) are proposed. The Long-Term Pavement Performance (LTPP) database is used for the models development and validation. Data from 89 LTPP sections including 617 observations from the Specific Pavement Studies (SPS-1) with no maintenance activities are collected. These data cover the four climatic zones (wet, wet freeze, dry, and dry freeze) in the USA, different pavement structures, and different levels of traffic loading. Based on these data, PCI prediction models are developed using two modeling approaches: multiple linear regression analysis and artificial neural networks (ANNs). The proposed models predict the PCI as a function of climatic factors, namely average annual temperature, standard deviation of monthly temperature, precipitation, wind speed, freezing index, total pavement thickness, and weighted plasticity index. Additionally, traffic loading, expressed in terms of the classical equivalent single-axle loads, is considered. The regression model yielded a coefficient of determination (R2) value of 0.80, whereas the ANNs model results in a relatively higher R2 value of 0.88. The proposed models are not only simple and accurate; they also have the potentials of being adopted in countries experiencing similar climatic conditions and traffic loading.

Rutting resistance of toner-modified asphalt binder and mixture

Asphalt binder resistance to permanent deformation considerably influences total pavement resistance to rutting at the high service temperatures. To improve asphalt shear strength against rutting resistance, researchers have been used various modifiers and recently the use of waste materials as binder rheological enhancement agents is paid lots of attention. In this study, waste toner was adopted as an anti-rutting enhancement agent, and then neat asphalt binder was modified by waste toner at four dosages: 4, 8, 12 and 16% based on asphalt binder’s weight. The effectiveness of binder modification by waste toner to improve asphalt binder and mixture’s resistance to permanent deformation has been assessed by means of different met hods: the Superpave specification parameter, G*/sinδ, and the multiple stress creep and recovery (MSCR) test for asphalt binder and wheel track test for asphalt mixture to determine the rut depth for a certain number of loadings. Results showed that adding toner to neat asphalt binder can meaningfully enhance the anti-rutting performance of asphalt binder and subsequently asphalt mixture. Moreover, increasing the dosage of toner up to 12% in the modified asphalt binder amplifies the trend of rutting resistance improvement.