LTPP pavement maintenance materials : SHRP joint reseal experiment, final report /

"September 1999."

Pavement maintenance management.

"November 1982."

Optimization of pavement maintenance and rehabilitation programming using shuffled complex evolution algorithm

The major barrier to practical optimization of pavement preservation programming has always been that for formulations where the identity of individual projects is preserved, the solution space grows exponentially with the problem size to an extent where it can become unmanageable by the traditional analytical optimization techniques within reasonable limit. This has been attributed to the problem of combinatorial explosion that is, exponential growth of the number of combinations. The relatively large number of constraints often presents in a real-life pavement preservation programming problems and the trade-off considerations required between preventive maintenance, rehabilitation and reconstruction, present yet another factor that contributes to the solution complexity. In this research study, a new integrated multi-year optimization procedure was developed to solve network level pavement preservation programming problems, through cost-effectiveness based evolutionary programming analysis, using the Shuffled Complex Evolution (SCE) algorithm.^ A case study problem was analyzed to illustrate the robustness and consistency of the SCE technique in solving network level pavement preservation problems. The output from this program is a list of maintenance and rehabilitation treatment (M&R) strategies for each identified segment of the network in each programming year, and the impact on the overall performance of the network, in terms of the performance levels of the recommended optimal M&R strategy. ^ The results show that the SCE is very efficient and consistent in the simultaneous consideration of the trade-off between various pavement preservation strategies, while preserving the identity of the individual network segments. The flexibility of the technique is also demonstrated, in the sense that, by suitably coding the problem parameters, it can be used to solve several forms of pavement management programming problems. It is recommended that for large networks, some sort of decomposition technique should be applied to aggregate sections, which exhibit similar performance characteristics into links, such that whatever M&R alternative is recommended for a link can be applied to all the sections connected to it. In this way the problem size, and hence the solution time, can be greatly reduced to a more manageable solution space. ^ The study concludes that the robust search characteristics of SCE are well suited for solving the combinatorial problems in long-term network level pavement M&R programming and provides a rich area for future research. ^

A methodological framework for modeling pavement maintenance costs for projects with performance-based contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

A Methodological Framework for Modeling Pavement Maintenance Costs for Projects with Performance-based Contracts

Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Field Performance and Evaluation of Slurry Seals, HR-195, 1980

As part of the overall research program of evaluating asphalt emulsion slurry seal as a pavement maintenance material, 31 duplicate 500-ft test sections were constructed on U.S. 6 between Adel and Waukee in Dallas County during September and October of 1978. These test sections included combinations of eight aggregates, two gradings, three asphalt emulsions, two mineral fillers, and a range of emulsion contents determined by laboratory mix designs. The emulsion contents of the test sections varied from 10.3% for Section 7A (Ferguson coarse) to 32.9% for Section 31A (lightweight aggregate). The post-construction performance evaluation of the test sections, consisting primarily of the friction tests and surface appearance observations, was conducted at different time intervals up to 24 months after construction. At the 24-month final evaluation, most of the test sections had carried a total of 1.4 million vehicles.

The AASHO road test: report.

National Research Council. Publication 816, 951-955, 1061.

Development of a Wireless MEMS Multifunction Sensor System and Field Demonstration of Embedded Sensors for Monitoring Concrete Pavements, TR-637, 2016

Pavements tend to deteriorate with time under repeated traffic and/or environmental loading. By detecting pavement distresses and damage early enough, it is possible for transportation agencies to develop more effective pavement maintenance and rehabilitation programs and thereby achieve significant cost and time savings. The structural health monitoring (SHM) concept can be considered as a systematic method for assessing the structural state of pavement infrastructure systems and documenting their condition. Over the past several years, this process has traditionally been accomplished through the use of wired sensors embedded in bridge and highway pavement. However, the use of wired sensors has limitations for long-term SHM and presents other associated cost and safety concerns. Recently, micro-electromechanical sensors and systems (MEMS) and nano-electromechanical systems (NEMS) have emerged as advanced/smart-sensing technologies with potential for cost-effective and long-term SHM. This two-pronged study evaluated the performance of commercial off-the-shelf (COTS) MEMS sensors embedded in concrete pavement (Final Report Volume I) and developed a wireless MEMS multifunctional sensor system for health monitoring of concrete pavement (Final Report Volume II).

Maintenance of Pavement Skid Resistance (Open Graded Asphalt Friction Courses), Progress Report, HR-170, 1976

This project involved the evaluation of several aggregates previously rated poor to excellent with respect to skid resistance and certain mix design parameters. An open graded asphalt friction course was evaluated using 4 comparably graded aggregates: quartzite, fine grained limestone, coarse limestone and lightweight expanded shale. The performance investigations involved the verification of observations of the quartzite test sections, evaluation of the effect of blending the superior quartzite with a typical coarse grained-textured limestone, and the evaluation of the limestone. The effects of traffic on the aggregates used in the test sections were studied, as well as the relationship between asphalt content levels and traffic with respect to performance. The bond of the open graded friction course mixture was also evaluated. The SN performance of all test sections after sixteen months of exposure was found to be satisfactory in that none of the material combinations had polished to the point where unacceptable SN levels developed. When material combinations were compared, significant differences were noted.

Instrumentation for measuring pavement-vehicle interaction. Volume I: system description, operation, calibration and maintenance manual. Final report.

Federal Highway Administration, Structures and Applied Mechanics Division, Washington, D.C.

Instrumentation for measuring pavement-vehicle interaction. Volume II: Digalog Systems operation and maintenance manual, data acquisition system, model DLI 203. Final report.

Federal Highway Administration, Structures and Applied Mechanics Division, Washington, D.C.

Instrumentation for measuring pavement-vehicle interaction. Volume III: Kennedy Co. operation and maintenance manual, formatter and digital tape transport. Final report.

Federal Highway Administration, Structures and Applied Mechanics Division, Washington, D.C.

Rigid pavements distresses - pavement condition index evaluation

Pavements require maintenance in order to provide good service levels during their life period. Because of the significant costs of this operation and the importance of a proper planning, a pavement evaluation methodology, named Pavement Condition Index (PCI), was created by the U.S. Army Corps of Engineers. This methodology allows for the evaluation of the pavement condition along the life period, generally yearly, with minimum costs and, in this way, it is possible to plan the maintenance action and to adopt adequate measures, minimising the rehabilitation costs. The PCI methodology provides an evaluation based on visual inspection, namely on the distresses observed on the pavement. This condition index of the pavement is classified from 0 to 100, where 0 it is the worst possible condition and 100 the best possible condition. This methodology of pavement assessment represents a significant tool for management methods such as airport pavement management system (APMS) and life-cycle costs analysis (LCCA). Nevertheless, it has some limitations which can jeopardize the correct evaluation of the pavement behavior. Therefore the objective of this dissertation is to help reducing its limitations and make it easier and faster to use. Thus, an automated process of PCI calculation was developed, avoiding the abaci consultation, and consequently, minimizing the human error. To facilitate also the visual inspection a Tablet application was developed to replace the common inspection data sheet and thus making the survey easier to be undertaken. Following, an airport pavement condition was study accordingly with the methodology described at Standard Test Method for Airport Pavement Condition Index Surveys D5340, 2011 where its original condition level is compared with the condition level after iterate possible erroneous considered distresses as well as possible rehabilitations. Afterwards, the results obtained were analyzed and the main conclusions presented together with some future developments.

Investgiation into Improved Pavement Curing Materials and Techniques: Part 1 - Phases I and II, April 2002

Concrete curing is closely related to cement hydration, microstructure development, and concrete performance. Application of a liquid membrane-forming curing compound is among the most widely used curing methods for concrete pavements and bridge decks. Curing compounds are economical, easy to apply, and maintenance free. However, limited research has been done to investigate the effectiveness of different curing compounds and their application technologies. No reliable standard testing method is available to evaluate the effectiveness of curing, especially of the field concrete curing. The present research investigates the effects of curing compound materials and application technologies on concrete properties, especially on the properties of surface concrete. This report presents a literature review of curing technology, with an emphasis on curing compounds, and the experimental results from the first part of this research—lab investigation. In the lab investigation, three curing compounds were selected and applied to mortar specimens at three different times after casting. Two application methods, single- and double-layer applications, were employed. Moisture content, conductivity, sorptivity, and degree of hydration were measured at different depths of the specimens. Flexural and compressive strength of the specimens were also tested. Statistical analysis was conducted to examine the relationships between these material properties. The research results indicate that application of a curing compound significantly increased moisture content and degree of cement hydration and reduced sorptivity of the near-surface-area concrete. For given concrete materials and mix proportions, optimal application time of curing compounds depended primarily upon the weather condition. If a sufficient amount of a high-efficiency-index curing compound was uniformly applied, no double-layer application was necessary. Among all test methods applied, the sorptivity test is the most sensitive one to provide good indication for the subtle changes in microstructure of the near-surface-area concrete caused by different curing materials and application methods. Sorptivity measurement has a close relation with moisture content and degree of hydration. The research results have established a baseline for and provided insight into the further development of testing procedures for evaluation of curing compounds in field. Recommendations are provided for further field study.