Impact of Rainfall on Flexible Pavement Performance Models for Texas Highways

Impact of Rainfall on Flexible Pavement Performance Models for Texas Highways
Author: K. M. Saifur Rahman
Publisher:
Total Pages: 183
Release: 2015
Genre: Pavements
ISBN: 9781339034737

One of the main elements of any Pavement Management System is Pavement Performance Modeling. Accurate pavement performance models can save millions of dollars through proper maintenance of the transportation pavement infrastructure. Several pavement performance models have been developed over the years to predict pavement performance. However, in the development of pavement performance models the climatic parameters were often ignored. Climatic inputs, especially rainfall, affect pavement performances because material properties change with temperature and moisture conditions particularly in ACP (Asphalt Concrete Pavement). The modulus of the unbound materials is sensitive to the variation of moisture content. Rainwater can infiltrate into the unsaturated pavement layers though cracks, joints or edges of the pavement and can deteriorate the pavement structure by reducing structural capacity. This study investigates rainfall impacts on pavement performance and maintenance costs of asphalt concrete pavement on Texas highways. Performance models are developed to accurately predict the pavement condition and performance for the Texas Department of Transportation (TXDOT) Highway pavement network for San Antonio Districts. In addition, tools are developed to accurately estimate the future maintenance cost considering rainfall. TxDOT's PMIS data for the San Antonio Texas Department of Transportation (TxDOT) District was used for pavement conditions and NOAA data was used for historical rainfall information. One Way Analysis of Variance (ANOVA) was performed to determine the significant variables for the pavement performance model. The San Antonio District's road network broken into five pavement families following functional classes such as Interstate Highways (IH) main lane, Interstate Highways (IH) frontage lane, State Highways (SH), US highways (US) and Farm to Market Road (FM). The statistical modeling reported herein shows that rainfall had a significant impact on deterioration of pavement conditions of Interstate Highways (IH) for main lanes. For Interstate Highways (IH) frontage lane and Farm to Market (FM) pavement families combination of rainfall and traffic class had significant impact on the pavement performance model. Engineering knowledge supported the concept that increasing amount of rainfall will degrade the pavement structure at a faster rate. However, statistical analysis of the available data showed that rainfall did not have a significant statistical impact on the performance model of State Highway (SH) and US highways (US) pavement families. Other significant factors that affect the flexible pavement performance identified in this research for all pavement types are pavement age and previous year's distress scores. Previous maintenance and rehabilitation (M&R) activities performed on a pavement section will also have a significant impact on the pavement deterioration model for pavement families except for Interstate Highway (IH) main lanes and U.S Highways (US). In this research, an application was developed to estimate the maintenance cost of the network considering the rainfall and other significant factors. This tool will allow users to accurately predict future maintenance costs and allocate appropriate budgets.

Texas Flexible Pavements and Overlays

Texas Flexible Pavements and Overlays
Author: Sang Ick Lee
Publisher:
Total Pages: 90
Release: 2017
Genre: Information storage and retrieval systems
ISBN:

Proper calibration and validation of pavement design and performance models to Texas conditions is essential for cost-effective flexible pavement design, performance predictions, and maintenance/rehab strategies. The veracity of the calibration of the Texas Department of Transportation pavement design models will determine how optimally billions of dollars of future roadway investment capital will be spent. For proper calibration/validation and tangible benefits, quality and reliable pavement performance data should be collected on a sustained basis. In order to accomplish the task of data collection, this five-year project was initiated to develop a comprehensive data storage system (DSS) of material properties and performance data for Texas flexible pavements and overlays. The objective of the project was to collect materials and pavement performance data on a minimum of 100 highway test sections around Texas. In total, the SS comprises 112 highway test sections scattered across Texas. This report documents all the work performed, methods used, and results ompleted throughout the project. These tasks included gathering design and construction data of test sections, executing laboratory and field performance testing, collecting traffic and climate data, and developing the data repository system consisting of the DSS and a raw data storage system (RDSSP). Finally, recommendations for the continuation of data collection to enable further calibration of performance models are given.

Effects of Climatic Loading in Flexible Pavement Subgrades in Texas

Effects of Climatic Loading in Flexible Pavement Subgrades in Texas
Author: Asif Ahmed
Publisher:
Total Pages: 206
Release: 2017
Genre: Pavement performance
ISBN:

Expansive soils, which have been reported as a worldwide problem, cover 25% of the United States. Due to the swelling and shrinkage behavior induced by moisture variations, expansive soil contributes to volumetric deformation, which in turn affects the stability and performance of structures. The Texas Department of Transportation (TxDOT) allocates 25% of its budget to pavement maintenance and repairs, much of which is triggered by expansive soil. In order to decrease the burden of this expense on maintenance authorities, it is necessary to have an accurate understanding of expansive subgrade behavior. Applying this knowledge to the pavement design and construction processes can significantly increase the pavement's service life. The specific objectives of this research were to (1) study the behavior of expansive soil with seasonal changes and climatic loading; (2) asses the real-time moisture and temperature variations in the expansive subgrade; (3) quantify the deformation pattern with time in response to environmental loading; (4) develop a realtime moisture, temperature, and deformation prediction model; (5) based on the investigation of the subgrade, provide solutions in order to combat the pavement deformation; and (6) evaluate the effectiveness of the proposed solution. In order to accomplish the objectives, one farm-to-market road and one state highway were selected for observation of the behavior of expansive subgrades in North Texas. Soil samples were collected and tested to determine the soil properties. Moisture, suction sensors, temperature sensors, and rain gauges were installed to record the variations of the variables over time. Moreover, geophysical testing was conducted to continually portray the subgrade over time. Deformation of the pavement was monitored through topographic surveying and a horizontal inclinometer. Collected data was analyzed in a statistical environment to develop real-time prediction models. The first attempt produced a moisture variation model that captured variations due to seasonal effects and temporary variations due to rainfall. The outputs of this model were within 90% of the values measured on-site. The second attempt produced a temperature prediction model that was dependent on depth and the day of the year. The squared correlation coefficient between the observed and predicted soil temperature was more than 0.90. Application of the developed models could allow for a non-invasive estimation of the response of soil strength and stiffness properties due to variations in moisture and temperature. While examining the deformation data, it was found that seasonal variations only capture a portion of the deformation, whereas the amount of precipitation plays a significant role in further modifying the model. Temperature and suction were also correlated with deformation to finalize the deformation model. Application of the developed model facilitates estimation of deformation at any time of the year, in response to precipitation. The study also attempted to focus, to a limited extent, on numerical modeling; however, the selection of unsaturated parameters was challenging. The selection of unsaturated permeability and flow parameters is usually laboratory-based, because a specific condition of the soil makes it impossible to capture them in real time in the field. This study attempted to determine the variations of unsaturated hydraulic conductivity based on rainfall response data. Rather than conducting the usual laboratory testing to determine the unsaturated flow parameters by curve fitting, a novel approach was undertaken to determine the flow parameters from field soil water characteristic curves. Finally, field-based values were used in the PLAXIS 2D environment for transient analysis. The validity of the estimated parameters was confirmed, as FE results corresponded with direct field measurements. The study results indicated that FE modeling can provide effective information about the subgrade matric suction variations. This research focused on finding a possible solution to the problem of pavement distress. It was found that controlling the moisture from the edge of the pavement can significantly improve the pavement performance. Consequently, a moisture barrier consisting of a geomembrane and a geocomposite (geonet sandwiched between two nonwoven geotextiles) was suggested. A combination of a 40-mil LLDPE geomembrane and an 8-oz. HDPE geocomposite was used to control the moisture from the edge of a 50 ft. section of FM 987. A control section along the same roadway was instrumented and monitored for comparison. Preliminary field monitoring results clearly indicated that the moisture barrier significantly reduced the water infiltration near the edge of the pavement. Moreover, the movement of the pavement was reduced by 80%, based upon previous recorded measurements of the control section.

Texas Flexible Pavements and Overlays

Texas Flexible Pavements and Overlays
Author: Sang Ick Lee
Publisher:
Total Pages: 86
Release: 2017
Genre: Information storage and retrieval systems
ISBN:

This five--year project was initiated to collect materials and pavement performance data on a minimum of 100 highway test sections around the state of Texas, incorporating both flexible pavements and overlays. Besides being used to calibrate and validate mechanistic-empirical (M-E) design models, the data collected will also serve as an ongoing reference data source and/or diagnostic tool for Texas Department of Transportation engineers and other transportation professionals. Toward this goal, this second interim report provides documentation of the work performed from Year 1 through Year 5 of this project, focusing on Phases II and III activities, including the following: (a) collection, processing, and analysis of laboratory and field data; (b) data population and update in the data storage system (DSS) and raw data storage system for the project 0-6658 (RDSSP), respectively; (c) development of M-E calibration plans and guideline; and (d) preliminary calibration of the M-E models and software to Texas conditions using the collected data in the DSS.

Life-Cycle Civil Engineering: Innovation, Theory and Practice

Life-Cycle Civil Engineering: Innovation, Theory and Practice
Author: Airong Chen
Publisher: CRC Press
Total Pages: 1758
Release: 2021-02-26
Genre: Technology & Engineering
ISBN: 1000342042

Life-Cycle Civil Engineering: Innovation, Theory and Practice contains the lectures and papers presented at IALCCE2020, the Seventh International Symposium on Life-Cycle Civil Engineering, held in Shanghai, China, October 27-30, 2020. It consists of a book of extended abstracts and a multimedia device containing the full papers of 230 contributions, including the Fazlur R. Khan lecture, eight keynote lectures, and 221 technical papers from all over the world. All major aspects of life-cycle engineering are addressed, with special emphasis on life-cycle design, assessment, maintenance and management of structures and infrastructure systems under various deterioration mechanisms due to various environmental hazards. It is expected that the proceedings of IALCCE2020 will serve as a valuable reference to anyone interested in life-cycle of civil infrastructure systems, including students, researchers, engineers and practitioners from all areas of engineering and industry.

Flexible Pavement Condition-rating Model for Maintenance and Rehabilitation Selection

Flexible Pavement Condition-rating Model for Maintenance and Rehabilitation Selection
Author: Wael Elias Tabara
Publisher:
Total Pages: 0
Release: 2010
Genre:
ISBN:

Keeping asphalt-surfaced highways and roads in an acceptable condition is the major goal that departments of transportation and pavement engineers always strive to achieve. According to ASCE 2009 report card, an estimated spending of $186 billion is needed annually to substantially improve highways conditions. Hence, prediction models of current and future pavement condition should be rationalized and studied from cost effective perspective. In modeling the pavement condition, two major categories of models have been used: (1) deterministic and (2) stochastic. Existing models consider some factors that might be more critical than others, such as roughness measurements and distress information. They ignore other factors that could have a real effect on the accuracy of the pavement performance model(s), such as climate conditions. Therefore, the current research aims at developing a comprehensive condition-rating model that incorporates a wider range of possible factors significantly affecting flexible pavement performance. Data for this research were collected from the records of Nebraska Department of Roads (NDOR) called "Tab Files". In addition to a questionnaire that was designed and sent to pavement engineers and experts in North America. An integrated model was developed using Multi-Attribute Utility Theory (MAUT) and multiple regression analysis. Sensitivity analysis of the developed regression models is done using Monte-Carlo simulation to quickly identify the high-impact factors. Models' validation shows robust results with an average validity percent of 94% in which they can be utilized by Departments of Transportation (DOT) and/or Pavement Management Systems (PMS) as a useful tool for assessing and predicting pavement conditions.