Este trabalho apresenta o desenvolvimento e a adaptação de modelos de previsão de desempenho aos fatores que condicionam as atividades de manutenção e reabilitação dos pavimentos nas cidades brasileiras de médio porte. Faz-se uma revisão bibliográfica sobre Sistemas de Gerência de Pavimentos e modelos de desempenho. Realiza-se um estudo de caso com seções selecionadas na rede pavimentada urbana de Araraquara-SP, exemplo de cidade brasileira de· médio porte. São desenvolvidos dois tipos de modelos: modelos empíricos, baseados em análises estatísticas de dados de pavimentos; e modelos subjetivos, com o desenvolvimento de matrizes de probabilidades de transição a partir de métodos formais de entrevistas com especialistas. Analisa-se a influência dos seguintes fatores sobre o desempenho de pavimentos urbanos: ano de construção, classificação funcional, atividades de manutenção e reabilitação, tráfego e estrutura do pavimento. Verifica-se uma significativa influência das atividades de manutenção e reabilitação. Nota-se, também, a necessidade de calibração periódica dos modelos de desempenho. Sugere-se a manutenção de arquivos de dados com informações sobre os fatores que afetam o desempenho dos pavimentos urbanos e sobre avaliações frequentes da condição dos pavimentos. / This work presents the development of performance prediction models, considering the factors that govern the programming of pavement maintenance and rehabilitation in Brazilian medium-sized cities. A bibliographic revision about Pavement Management Systems and performance models is pointed out. It is shown a case study with sections selected in the urban pavement network of Araraquara-SP, example of Brazilian medium-sized city. Two types of performance prediction models are developed: empirical models, based on statistics analyses of pavement data; and subjective models, based on the development of transition probability matrices from expert opinions. It is investigated the influence of the following factors on the performance of urban pavements: year of construction, functional category, maintenance and rehabilitation activities, traffic, and pavement structure. An expressive influence of the factor maintenance and rehabilitation activities is verified. It is also noticed the necessity of periodic calibration of the performance models. Maintenance of data files with information about the factors that act on the performance of urban pavements, and about frequent evaluations of the pavement condition is suggested.

Este trabalho apresenta o desenvolvimento e a adaptação de modelos de previsão de desempenho aos fatores que condicionam as atividades de manutenção e reabilitação dos pavimentos nas cidades brasileiras de médio porte. Faz-se uma revisão bibliográfica sobre Sistemas de Gerência de Pavimentos e modelos de desempenho. Realiza-se um estudo de caso com seções selecionadas na rede pavimentada urbana de Araraquara-SP, exemplo de cidade brasileira de· médio porte. São desenvolvidos dois tipos de modelos: modelos empíricos, baseados em análises estatísticas de dados de pavimentos; e modelos subjetivos, com o desenvolvimento de matrizes de probabilidades de transição a partir de métodos formais de entrevistas com especialistas. Analisa-se a influência dos seguintes fatores sobre o desempenho de pavimentos urbanos: ano de construção, classificação funcional, atividades de manutenção e reabilitação, tráfego e estrutura do pavimento. Verifica-se uma significativa influência das atividades de manutenção e reabilitação. Nota-se, também, a necessidade de calibração periódica dos modelos de desempenho. Sugere-se a manutenção de arquivos de dados com informações sobre os fatores que afetam o desempenho dos pavimentos urbanos e sobre avaliações frequentes da condição dos pavimentos. / This work presents the development of performance prediction models, considering the factors that govern the programming of pavement maintenance and rehabilitation in Brazilian medium-sized cities. A bibliographic revision about Pavement Management Systems and performance models is pointed out. It is shown a case study with sections selected in the urban pavement network of Araraquara-SP, example of Brazilian medium-sized city. Two types of performance prediction models are developed: empirical models, based on statistics analyses of pavement data; and subjective models, based on the development of transition probability matrices from expert opinions. It is investigated the influence of the following factors on the performance of urban pavements: year of construction, functional category, maintenance and rehabilitation activities, traffic, and pavement structure. An expressive influence of the factor maintenance and rehabilitation activities is verified. It is also noticed the necessity of periodic calibration of the performance models. Maintenance of data files with information about the factors that act on the performance of urban pavements, and about frequent evaluations of the pavement condition is suggested.

This study aimed at investigating the current practices and methods adopted by roads agencies around the world with regard to collection, analysis and utilization of the data elements pertaining to the main pavement condition indicators in pavement management systems (PMS). It also aimed at identifying the main predictors associated with each condition indicator and the factors that govern pavement structural and functional performance. Development of a new performance index that incorporates parameters or measures related to the main condition indicators (surface defects, roughness, deflection and skid resistance) and establishing the weight to be assigned to each indicator based on the relative impact on pavement condition was also one of the main objectives of this study. Thousands of pavement sections were subjected to thorough testing and inspection over the last few years to collect data pertaining to the main condition indicators. The collected data encompass visual distress survey, deflection measurements, roughness and skid resistance measurements. Collection of various condition indicators was accomplished according to well known international standards. The collected data were processed, tabulated and analyzed for the purpose of development of performance models and to prove certain theories or good practices. / Advanced tools and machines were utilized to collect these data with a high degree of accuracy. The Falling Weight Deflectometer (FWD) was used to collect deflection data for structural analysis. Two Non-contact laser roughness measuring devices mounted on vehicles were heavily used for collecting roughness, texture, and rutting data. Distress data were collected using a manual procedure adopted and standardized at the Pavement Management System Unit of Dubai Emirate. Powerful engineering and statistical softwares were used in the analysis for the purpose of processing the data, back calculating the main parameters pertaining to pavement response, establishing the correlation matrices between various dependent variables and their predictors, and finally, applying linear and non linear regression analysis to develop reliable and predictable deterioration models for the uses of pavement management system. The analysis procedure was supplemented by a vast literature review for the up to date information along within deep investigations and verifications for some of the current practices, theories and models used in pavement design and pavement evaluation with more emphasis on the inherent drawbacks associated to these models and procedures. The study confirmed that pavement condition deterioration and performance can be best predicted and evaluated based on four main condition indicators; First, surface distress to assess the physical condition of the pavements and detect the inherent problems and defects caused by various factors affecting pavement performance. Second; roughness measurements to evaluate the riding quality of the pavement. / Third; deflection to calculate pavement response (stress and strains) and to assess pavement structural capacity and calculating the remaining life, and finally, skid resistance measurement to assess the level of safety and surface texture properties. Thorough study and investigation of the physical condition indicators and the associated parameters, confirmed that pavement distress data are vital elements in each pavement management system. Distress data can be used effectively to identify the main problems associated with pavement performance, causes of deterioration, maintenance measures needed to prevent the acceleration of the distress, the rehabilitation schemes needed to improve the pavement condition and finally to prepare maintenance work programs and to estimate the annual maintenance needs under an open or limited budget. Alligator cracking was found to have the heaviest impact on pavement condition. Distress density, probable causes of deterioration and distress propagation rate are the required parameters in PMS. Roughness was found to have a basic influence on pavement condition and the type of selected treatment. The use of Roughness data in terms of International Roughness Index (IRI) can be optimized in PMS by using this indicator in the following forms: / Roughness, as an objective measure, can be used as a good performance predictor of the current riding quality of pavements in service and reflects the inherent imperfections and built-in irregularities embodied in the road pavement surface. Roughness measurement can be used as a reference to establish construction specifications and provides through the PMS system an organized feedback approach to correct the persistent design deficiencies detected after road construction. Roughness can be used effectively in the planning process for maintenance works and to select the candidate sections through calculating the functional remaining life based on the estimated terminal value using Roughness-Age, Roughness-ESAL, and Roughness-PSI models. Lane–IRI along with the Difference between the left and right wheel IRI values, termed as “ Yaw” are the most suitable forms to be used in PMS to report about roughness characteristics. Yaw term can be used effectively to report or feed back about geometric imperfections that exist on the road surface such as improper cross slope, shoving and the probable drainage problems. The roughness cumulative distribution curves can be used as a planning tool in PMS to report at the network level. These curves indicate the network health and the required funding at different level of risks, so proactive measures can be taken and the required budgets can be made available. / Deflection data were found to form a basic component of the PMS. It was found that these data can be used at both network and project levels. Direct deflection measurements were found Not to be the ideal form to report about structural capacity at the network level. It is rather can be used at project level to detect weak spots and critical pavements layers. At the network level, the back calculated parameters from deflection basin such as Pavement Modulus (Ep), Asphalt and Pavement Curvature (CUR), Cross Sectional Area and the other deflection basin characteristics are much more appropriate for reporting about pavement structural conditions and calculating the structural remaining life in PMS. The design deflection and curvature that characterize the pavement have been found to be calculated based on the mean along with the two times the standard deviation of the measured data. The Effective Structural Number (SNeff) was found to have good correlations with the Total Pavement Thickness (Ht), the value of the deflection measured at the center of the loading plate ( D0 ) and the difference between D0 and the deflection measured at 450mm from the center of the loading plate ( D0 - D450 ). The first two variables were found to account for more than 92% of the structural capacity prediction model. / Traffic variable in terms of the accumulated standard repetitions (ESAL) was found to account for more than 60% of the deflection model predictability. Other variables such as E value, asphalt and base layer thicknesses can improve the predictability of the model if included. The concept of the relative value of effective pavement modulus to the original pavement modulus (Eeff/E0) was found to gives a reliable representation about the exhausted and the remaining life of the in-service pavement structure. The study showed that the pavement is reported to be structurally failed, when the effective asphalt or pavement modulus is about 20 - 35 % of its original design value which is equal to the modulus of the unbound material. It was also found that when the area of the fatigue cracking and the patching distresses exceeds 17% of the total pavement section area, or the depth of rutting is more than 15mm, the pavement is reported to be structurally failed and major rehabilitation or reconstruction should be applied. Skid resistance can be reported in the form of International Friction Index (IFI), as a well defined universal index, along with other two numbers; F60 Friction (Microtexture) related number measured at 60 km/h velocity and Macrotexture related number and Vp, which constitute the IFI index can be used in Pavement management system applications to report about skid resistance characteristics and the network level of safety. These three figures can be used to report about pavement condition, accidents, airports operations, and maintenance management surveys. / In this study, new methods and models were developed and suggested to be used in PMS as an alternative to the current available methods which were found to be impractical in certain cases. Finally, further research efforts are recommended to explore the uses of other parameters in particular those related to deflection basin analysis, cross sectional area, curvature, and pavement moduli. Skid resistance testing and reporting method should be subjected to further research works for the purpose of standardizing reporting methods, identifying the relative impact of main predictors i.e. megatexture, macrotexture and microtexture components and to develop performance models.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / A pavement management system (PMS) is a tool that supports decision-making specialists to maintain the pavement at an optimal service level. The absence of a PMS could lead to inadequate decision-making, a disorganized road inventory, poor selection in road maintenance techniques and inefficient technical support to justify the execution of maintenance activities. For these reasons, this research proposes the application of a PMS, with the objective of improving and standardizing the processes for evaluating the condition of roads that are under the jurisdiction of low-budget government organizations, guaranteeing the selection of the most appropriate type of maintenance. As a case of study, a 1.1 km local road located in one of the districts of Lima was evaluated, which was divided into 11 sections. With this evaluation, it was obtained that 2,605.43 m2 of the total road is in poor condition, due to the presence of functional failures. For the identification of failures, the pavement condition index (PCI), the international roughness index (IRI) and the present serviceability index (PSI) were used to determine the condition, roughness and serviceability of the pavement. In conclusion, it was identified that the proposed PMS is adequately adapted to the way of working and available budget of a local administration, since if it is applied it would only spend 20.55% of the fund that would be destined to a total reconstruction of road.

Preventive maintenance has the potential to improve network condition by retarding future pavement deterioration. The Virginia Department of Transportation uses its pavement management system to determine maintenance targets for each district. The districts then use these recommendations to select pavements that will receive maintenance and the types of treatments that will be applied. Each district has a different approach to preventive maintenance. There was a need for more consistent preventive maintenance practices across the state. This thesis outlines guidelines for the implementation of a preventive maintenance policy. Preventive maintenance treatments currently being used within Virginia include chip seal, slurry seal, microsurfacing, and thin hot mix asphalt overlays. Historical pavement condition data was obtained from the VDOT PMS for these treatments and treatment performance models were developed. A district level treatment selection tool was developed to assist the district level decision making process. A prioritized list of pavement sections was generated, maximizing the cost-effectiveness of the selected treatments subject to budgetary constraints set by the central office. The treatment selection tool was then run for each pavement classification in each district. The results of this analysis were presented. Although the recommended budget for each district was very close to the targets set by the central office, the recommended lane miles for each district were about half the targets set by the central office.  It is believed that the unit costs used in this analysis were higher than those used in the VDOT PMS analysis. This selection tool has the potential to be a very powerful decision support tool if the unit costs are representative of what the expected treatment costs are for each district. / Master of Science

京都大学 / 0048 / 新制・論文博士 / 博士(工学) / 乙第12982号 / 論工博第4129号 / 新制||工||1637(附属図書館) / 32452 / (主査)教授 小林 潔司, 教授 大津 宏康, 教授 河野 広隆 / 学位規則第4条第2項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

No description available.

Sustainable pavement management implies maintaining acceptable condition of pavements while also considering the tradeoff between cost, environmental impacts and social impacts of pavement investments. Typical pavement management practices only consider economic considerations, and environmental mitigation techniques are employed after the selection of the maintenance action is complete. This dissertation presents a series of papers that demonstrate the impact of decision making on the environmental impact of the pavements both at the project and network levels of pavement management. An analysis was conducted of two models that relate pavement properties to vehicle rolling resistance and fuel consumption. These models were used, along with other tools to evaluate the impact of including the use phase of a pavement into pavement lifecycle assessments. A detailed project level lifecycle assessment was conducted, and it was found that the vehicles on the pavement during the use phase contribute the most to environmental pollutants by a significant margin over other phases of the lifecycle. Thus, relatively small improvements in the factors which contribute to rolling resistance may significantly influence the environmental impacts of the pavement. Building on this, a network level lifecycle assessment method was proposed to probabilistically quantify energy consumption for a given set of expected maintenance actions. It was shown that, although maintenance actions require a certain amount of energy consumption, this energy can be offset by improved road conditions leading to reduced rolling resistance. However, this tradeoff of reduced energy consumption also includes increased costs for a given network condition. In other words, the lowest energy consumption values did not tend to fall along the line defined by minimizing the cost divided by the pavement condition. In order to demonstrate how this tradeoff should be addressed, a novel decision analysis framework was developed, and implemented on a specific pavement network. Finally, a survey of transportation professionals was evaluated to determine their optimal points within the solution space defined by minimizing costs and energy consumption while maximizing pavement condition. It was found that the solution space could be greatly reduced by implementing their responses using the proposed decision analysis framework. / Ph. D.

Doctor of Philosophy / Department of Civil Engineering / Mustaque A. Hossain / Remaining service life (RSL) has been defined as the anticipated number of years that a pavement will be functionally and structurally acceptable with only routine maintenance. The Kansas Department of Transportation (KDOT) has a comprehensive pavement management system, network optimization system (NOS), which uses the RSL concept. In support of NOS, annual condition surveys are conducted on the state highway system. Currently KDOT uses an empirical equation to compute RSL of flexible pavements based on surface condition and deflection from the last sensor of a falling-weight deflectometer (FWD). Due to limited resources and large size, annual network-level structural data collection at the same rate as the project level is impractical. A rolling-wheel deflectometer (RWD), which measures surface deflections at highway speed, is an alternate and fast method of pavement-deflection testing for network-level data collection. Thus, a model that can calculate RSL in terms of FWD first sensor/center deflection (the only deflection measured by RWD) is desired for NOS. In this study, RWD deflection data was collected under an 18-kip axle load at highway speed on non-Interstate highways in northeast Kansas in July 2006. FWD deflection data, collected with a Dynatest 8000 FWD on the KDOT network from 1998 to 2006, were reduced to mile-long data to match the condition survey data collected annually for NOS. Normalized and temperature-corrected FWD and RWD center deflections and corresponding effective structural numbers (SNeff) were compared. A nonlinear regression procedure in Statistical Analysis Software (SAS) and Solver in Microsoft Excel were used to develop the models in this study. Results showed that FWD and RWD center deflections and corresponding SNeff are statistically similar. Temperature-correction factors have significant influence on these variables. FWD data analysis on the study sections showed that average structural condition of pavements of the KDOT non-Interstate network did not change significantly over the last four years. Thus, network-level deflection data can be collected at four-year intervals when there is no major structural improvement. Results also showed that sigmoimal relationship exists between RSL and center deflection. Sigmoidal RSL models have very good fits and can be used to predict RSL based on center deflection from FWD or RWD. Sigmoidal equivalent fatigue crack-models have also shown good fits, but with some scatter that can be attributed to the nature and quality of the data used to develop these models. Predicted and observed equivalent transverse-crack values do not match very well, though the difference in magnitude is insignificant for all practical purposes.

Master of Science / Department of Civil Engineering / Mustaque A. Hossain / The objective of this research project was to assess the condition of general aviation airport pavements in Kansas. The study was also intended to form the basis for a pavement management system (PMS). A total of 137 runways from 107 airports across the state were surveyed. MicroPAVER, a PMS system developed by the U.S. Army Corps of Engineers, was selected as the platform for the PMS. An inventory database was developed for all runways in the network. Information about the construction and maintenance history was entered into the MicroPAVER database. On-site surveys were conducted between the months of May and July of 2008 to assess pavement conditions in terms of the Pavement Condition Index (PCI), following the methodology outlined by ASTM D 5340-04 and adopted by the Federal Aviation Administration (FAA). Approximately 68% of the sections surveyed were in “good” to “satisfactory” condition. Almost one-third of the network can be rated as “good.” About 21% of the sections studied were in “fair” condition. Overall, the condition of the network can be rated as “satisfactory.” A condition prediction curve was developed for each of the two different types of surfaces. From the prediction curves created using MicroPAVER, it was estimated that the number of branches rated as “good” could decrease by 50% by 2010. As much as 44% of the network could have a rating of “fair” by 2013 if the sections receive only routine maintenance. Two budget scenario comparison reports developed show that the 108 runways of the 78 general aviation airports eligible for FAA funding in Kansas could be brought to a “satisfactory” rating or above (i.e. average PCI ≥ 70) by spending approximately $15 million on average per year for the next five years.