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Author: Jianxiong Yu
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 200
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Book Description
Remaining service life estimation and pavement condition prediction are two essential functions of Pavement Management Systems. Survival curves are often developed to obtain remaining life of a pavement family at network level. Regression equations are often developed to predict future pavement condition at project level. The two objectives of this study are: (1) To develop the Cox Proportional Hazard model to analyze the effects of influential factors on pavement remaining life; (2) To develop linear mixed effects prediction model to improve the condition prediction accuracy for individual pavements. In this study, by specifying pavement condition rating (PCR) of 70 as the terminal pavement status, survival curves were developed based on historical PCR data using Cox Proportional Hazards method. Further, the estimated service lives of pavements were obtained from these survival curves. As an example, the survival data of asphalt overlays on flexible pavements in Ohio were analyzed for this study. The effects of influential factors such as structure thickness, climate, traffic loading, and pavement conditions prior to repair on pavement service life, were assessed. The results show that the Cox Proportional Hazards model is applicable in estimating the effects of influential factors on pavement service life. The service life obtained from this study can be used to assist in pavement rehabilitation decision-making, overlay design, and budget allocation. Condition prediction of individual pavement is usually required in project-level management and is often based on adjusting corresponding pavement family deterioration trend. This study proposes using the Linear Mixed Effects Model (LMEM) method to predict future conditions of a specific pavement section by a weighted combination of the deterioration trends of the family average and that of the specific pavement. The weights are determined by the number of historical condition measurements available and the variations of the measured historical conditions of the specific pavement. The results of the LMEM showed significantly better accuracy in predicting specific pavement conditions compared with two commonly used adjustment methods, which use the latest condition measurement to adjust family model for individual pavement. The findings in this study show that the LMEM is useful for project level pavement condition prediction.
Author: Jianxiong Yu
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 200
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Book Description
Remaining service life estimation and pavement condition prediction are two essential functions of Pavement Management Systems. Survival curves are often developed to obtain remaining life of a pavement family at network level. Regression equations are often developed to predict future pavement condition at project level. The two objectives of this study are: (1) To develop the Cox Proportional Hazard model to analyze the effects of influential factors on pavement remaining life; (2) To develop linear mixed effects prediction model to improve the condition prediction accuracy for individual pavements. In this study, by specifying pavement condition rating (PCR) of 70 as the terminal pavement status, survival curves were developed based on historical PCR data using Cox Proportional Hazards method. Further, the estimated service lives of pavements were obtained from these survival curves. As an example, the survival data of asphalt overlays on flexible pavements in Ohio were analyzed for this study. The effects of influential factors such as structure thickness, climate, traffic loading, and pavement conditions prior to repair on pavement service life, were assessed. The results show that the Cox Proportional Hazards model is applicable in estimating the effects of influential factors on pavement service life. The service life obtained from this study can be used to assist in pavement rehabilitation decision-making, overlay design, and budget allocation. Condition prediction of individual pavement is usually required in project-level management and is often based on adjusting corresponding pavement family deterioration trend. This study proposes using the Linear Mixed Effects Model (LMEM) method to predict future conditions of a specific pavement section by a weighted combination of the deterioration trends of the family average and that of the specific pavement. The weights are determined by the number of historical condition measurements available and the variations of the measured historical conditions of the specific pavement. The results of the LMEM showed significantly better accuracy in predicting specific pavement conditions compared with two commonly used adjustment methods, which use the latest condition measurement to adjust family model for individual pavement. The findings in this study show that the LMEM is useful for project level pavement condition prediction.
Author: Jack T. Allison
Publisher:
ISBN:
Category : Highway engineering
Languages : en
Pages : 338
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Book Description
Author: Eddie Chou
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages : 222
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Book Description
The primary objectives of this study were to develop models to forecast future pavement conditions and to determine remaining service life of pavements based on the forecasted conditions. Based on available data in the ODOT pavement database, which contains the condition history of each pavement section, along with its location, year of construction, thickness, materials used, climate, and rehabilitation records, individual regression, family regression, and Markov probabilistic models were developed . For the latter two models, pavements were first grouped into "families" with similar characteristics, based on pavement type, priority, District location, and past performance. Forecasting models were then developed for each such "family." The developed models were evaluated by comparing the predicted conditions with the actual observed conditions for the five year period between 2001 and 2005. The Markov model was found to have the highest overall prediction accuracy among all the models evaluated, and it can also predict future distresses in addition to the PCR values. As a result of this study, ODOT can forecast future pavement conditions and estimate the remaining service life of pavements. Future rehabilitation needs can also be determined. Such capabilities will significantly benefit planning and management decision-makings at both project and network levels
Author: Gulfam Jannat
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 183
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Book Description
Pavement Maintenance and Rehabilitation (M&R) are the most critical and expensive components of infrastructure asset management. Increasing traffic load, climate change and resource limitations for road maintenance accelerate pavement deterioration and eventually increase the need for future maintenance treatments. Consequently, pavement management programs are increasingly complex. The complexities are attributed to the precise assessment process of the overall pavement condition, realistic distress prediction and identification of cost-effective M&R schedules. Cost-effective road M&R practices are only possible when the evaluation of pavement condition is precise, pavement deterioration models are accurate, and resources must also be available at the right time. In a Pavement Management System (PMS), feasible M&R treatments are identified at the end of each branch of the decision trees. The decision trees are based on empirical relationships of the pavement performance index. Moreover, the predicted improvements in pavement performance for any treatment are set based on engineering experiences. Furthermore, the remaining service life of the pavement is estimated from the predicted deterioration of the overall condition. The future deterioration of the overall condition is estimated based on the initial condition and by considering only the effect of age notwithstanding the effect of traffic or materials. In assessing the overall condition of the pavement, this research overcomes the limitations of engineering judgment by incorporating a Mechanistic-Empirical (M-E) approach and estimating the improvement in performance for specific treatment types. It also considers the effect of traffic and materials on pavement performance to precisely predict its future deterioration and subsequent remaining service life. The objective of this research is to develop cost-effective pavement M&R schedules by incorporating (a) the M-E approach into the overall condition index and (b) the estimate of performance indices by considering the factors affecting pavement performance. The research objective will be accomplished by (i) incorporating variability analysis of existing performance evaluation practices and maintenance decisions of pavement, (ii) investigating estimates of existing performance indices, (iii) incorporating the M-E approach: sensitivity analysis, prediction, comparison and verification, (iv) estimating the deterioration model based on traffic characteristics and material types, and (v) identifying cost-effective M&R treatment options through Life Cycle Cost Analysis (LCCA). This study uses the pavement performance data of Ontario highways recorded in the Ministry of Transportation (MTO) pavement database. Precise assessment of pavement condition is a significant part in achieving the research goal. In a PMS, an accurate location reference system is necessary for managing pavement evaluations and maintenance. The length of the pavement section selected for evaluation may have a significant impact on the assessment irrespective of the type of performance indices. In Ontario, the highway section lengths range from 50m to 50,000m. For this reason, a variability in performance evaluation is investigated due to changes in section length. This study considers rut depth, Pavement Condition Index (PCI), and International Roughness Index (IRI) as performance indices. The distributions of these indices are compared by the following groupings of section lengths: 50m, 500m, 1,000m and 10,000m. The variations of performance assessments due to changing section lengths are investigated based on their impact on maintenance decisions. A Monte Carlo simulation is carried out by varying section lengths to estimate probabilities of maintenance work requirements. Results of such empirical investigations reveal that most of the longer sections are evaluated with low rut depth and the shorter sections are evaluated with high rut depth. This Monte Carlo simulation also reveals that 50m sections have a higher probability of maintenance requirements than 500m sections. The method of estimating performance indices is also investigated to identify the requirement of improvement in estimation of the prediction models. Generally, in a PMS, the prediction models of Key Performance Indicators (KPIs) are estimated by using the Ordinary Least Square (OLS) approach. However, the OLS approach can be inefficient if unobserved factors influencing individual KPIs are correlated with each other. For this reason, regression models for KPI predictions are estimated by using an approach called the 'Seemingly Unrelated Regression (SUR)' method. The M-E approach is used in this study to predict the future distresses by employing mechanistic-empirical models to analyze the impact of traffic, climate, materials and pavement structure. The Mechanistic-Empirical Pavement Design Guide (MEPDG) software uses a three-level hierarchical input to predict performance in terms of IRI, permanent deformation (rut depth), total cracking (reflective and alligator), asphalt concrete (AC) thermal fracture, AC bottom-up fatigue cracking and AC top-down fatigue cracking. However, these inputs have different levels of accuracy, which may have a significant impact on performance prediction. It would be ineffective to put effort for obtaining accuracy at Level 1 for all inputs. For this reason, a sensitivity analysis is carried out based on an experimental design to identify the effect of the accuracy level of inputs on the distresses. Following this, a local sensitivity analysis is carried out to identify the main effect of input variables. Interaction effects are also analyzed based on a random combination of the inputs. Since the deterioration of pavement is affected by site-specific traffic, local climate and properties of materials, these variables are carefully considered during the development of the pavement deterioration model to assess overall pavement conditions. The prediction model is developed by using a regression approach considering distresses of the M-E approach. In this study, the deterioration model is estimated for three groups of Annual Average Daily Traffic (AADT) to recognize their individual impact along with properties of materials. The time required for maintenance is also estimated for these categories. The investigations reveal that the expected time to maintenance for overlay with Dense Friction Course (DFC) and Superpave mixes is higher than other Hot Laid (HL) asphalt layers. This will help pavement designers and managers to make informed decisions. The probability of failure is also investigated by a probabilistic approach. With the increasing trend towards M&R of existing pavements, it is essential to make cost-effective use of the M&R budget. As such, identification of associated cost-effective M&R treatments is not always simple in most PMS. For this reason, a LCCA is carried out for alternate pavement treatments using the deterioration model based on traffic levels and material types. Comparing the Net Present Worth (NPW) value of alternative treatment options reveals that the overlay of pavement with DFC is the most cost-effective choice in the case of higher AADT. On the other hand, overlay with Hot Laid-1 (HL-1) is a cost-effective treatment option for highway sections with lower AADT. Although the results are related to the Ontario highway system, this can also be applied elsewhere with similar conditions. The outcome of the empirical investigations will result in the adoption of efficient road M&R programs for highways based on realistic performance predictions, which have significant impact on infrastructure asset management.
Author: M.Y. Shahin
Publisher: Springer
ISBN: 9780412992018
Category : Technology & Engineering
Languages : en
Pages : 450
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Book Description
Emphasizing sound, cost-effective management rather than emergency repairs, this comprehensive volume offers practical guidelines on evaluating and managing pavements for airports, roads, and parking lots. The author focuses on the implementation and maintenance of successful management strategies for both network and project levels, with repair techniques also described . Detailed chapters: 1) outline step-by-step procedures for project and network level pavement management 2) illustrate effective cost analysis and budget planning for pavement maintenance 3) guide the reader in the selection and use of non-destructive deflection, roughness measurement, and friction measurement equipment 4) present state-of-the-art pavement rehabilitation and condition prediction techniques 5) demonstrates the Pavement Condition Index (PCI) procedure for airfields and surfaced and unsurfaced roads. Extensive appendices serve as a field manual for identifying all types of pavement distress and their causes, and hundred of photographs facilitate accurate pavement evaluation. Civil and pavement engineers will find complete information on pavement inspection, evaluation, and management in this indispensable reference.
Author: John Harvey
Publisher: CRC Press
ISBN: 1000201724
Category : Technology & Engineering
Languages : en
Pages : 557
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Book Description
An increasing number of agencies, academic institutes, and governmental and industrial bodies are embracing the principles of sustainability in managing their activities. Life Cycle Assessment (LCA) is an approach developed to provide decision support regarding the environmental impact of industrial processes and products. LCA is a field with ongoing research, development and improvement and is being implemented world-wide, particularly in the areas of pavement, roadways and bridges. Pavement, Roadway, and Bridge Life Cycle Assessment 2020 contains the contributions to the International Symposium on Pavement, Roadway, and Bridge Life Cycle Assessment 2020 (Davis, CA, USA, June 3-6, 2020) covering research and practical issues related to pavement, roadway and bridge LCA, including data and tools, asset management, environmental product declarations, procurement, planning, vehicle interaction, and impact of materials, structure, and construction. Pavement, Roadway, and Bridge Life Cycle Assessment 2020 will be of interest to researchers, professionals, and policymakers in academia, industry, and government who are interested in the sustainability of pavements, roadways and bridges.
Author: Chaitanya Kumar Balla
Publisher:
ISBN:
Category : Pavements
Languages : en
Pages : 81
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Book Description
Pavement management is a process that helps to maintain a pavement network in a safe and serviceable condition in a cost effective manner. A key component of an effective pavement management system is its ability to predict the remaining service life of pavements. Remaining service life of pavements can be predicted using the present pavement condition and the latest rehabilitation action performed on that particular pavement. Survival curves are often developed to obtain remaining service life of a pavement family. The objectives of this study are to determine the average service life of pavements and to predict their remaining service life. Remaining Service Life is defined as the projected number of years until rehabilitation is required. The pavement condition data in the form of Pavement Condition Rating (PCR) were used to develop Kaplan-Meier survival curves for different PCR thresholds. PCR 60 was considered as the terminal condition and the average service life of pavement network was calculated as the area under PCR 60 survival curve. Derived performance curves for all the survival probabilities were developed between pavement age and PCR using the Weibull approximation of the Kaplan-Meier survival curves. Derived performance curves were employed to determine the remaining service life of individual pavements based on current age and PCR. PCR curves were also developed for individual PCR thresholds between RSL and pavement age by using the Weibull approximation of the Kaplan-Meier survival curves to better understand the relationship between RSL, PCR and pavement age. Average service life of the pavement network and remaining service life of individual pavements obtained from this study can be used to assist in pavement rehabilitation decision making and budget allocation.
Author:
Publisher:
ISBN:
Category : Hebrew language
Languages : en
Pages :
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Author: Jaroslav J. Hajek
Publisher: Transportation Research Board
ISBN: 0309143349
Category : Pavements
Languages : en
Pages : 112
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Book Description
TRB's Airport Cooperative Research Program (ACRP) Synthesis 22: Common Airport Pavement Maintenance Practices explores how airports implement a pavement maintenance management program, including inspecting and tracking pavement condition, scheduling maintenance, identifying necessary funds, and treating distresses in asphalt and concrete pavements.
Author: American Association of State Highway and Transportation Officials
Publisher: AASHTO
ISBN: 1560510552
Category : Pavements
Languages : en
Pages : 622
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Book Description
Design related project level pavement management - Economic evaluation of alternative pavement design strategies - Reliability / - Pavement design procedures for new construction or reconstruction : Design requirements - Highway pavement structural design - Low-volume road design / - Pavement design procedures for rehabilitation of existing pavements : Rehabilitation concepts - Guides for field data collection - Rehabilitation methods other than overlay - Rehabilitation methods with overlays / - Mechanistic-empirical design procedures.
