Crashes on wet pavements are responsible for 25% of all crashes and 13.5% of fatal crashes in the US (Harwood et al. 1988). This number represents a significant portion of all crashes. Current methods used by the Department of Transportations (DOTs) are based on wet over dry ratios and simplified approaches to estimate hydroplaning speeds. A fraction of all wet crashes is hydroplaning; although they are related, the difference between a "wet crash" and "hydroplaning" is a wet-crash hydrodynamic-based severity scale is less compared to hydroplaning where the driver loses control. This dissertation presents a new conceptual framework design to reduce wet- and hydroplaning-related crashes by identifying locations with a high risk of crashes using systemic, data-driven, risk-based approaches and available data. The first method is a robust systemic approach to identify areas with a high risk of wet crashes using a negative binomial regression to quantify the relationship between wet to dry ratio (WDR), traffic, and road characteristics. Results indicate that the estimates are more reliable than current methods of WDR used by DOTs. Two significant parameters are grade difference and its absolute value. The second method is a simplified approach to identify areas with a high risk of wet crashes with only crash counts by applying a spatial multiresolution analysis (SMA). Results indicate that SMA performs better than current hazardous-road segments identification (HRSI) methods based on crash counts by consistently identifying sites during several years for selected 0.1 km sections. A third method is a novel systemic approach to identify locations with a high risk of hydroplaning through a new risk-measuring parameter named performance margin, which considers road geometry, environmental condition, vehicle characteristics, and operational conditions. The performance margin can replace the traditional parameter of interest of hydroplaning speed. The hydroplaning risk depends on more factors than those identified in previous research that focuses solely on tire inflation pressure, tire footprint area, or wheel load. The braking and tire-tread parameters significantly affected the performance margin. Highway engineers now incorporate an enhanced tool for hydroplaning risk estimation that allows systemic analysis. Finally, a critical review was conducted to identify existing solutions to reduce the high potential of skidding or hydroplaning on wet pavement. The recommended strategies to help mitigate skidding and hydroplaning are presented to help in the decision process and resource allocation. Geometric design optimization provides a permanent impact on pavement runoff characteristics that reduces the water accumulation and water thickness on the lanes. Road surface modification provides a temporary impact on practical performance and non-engineering measures. / Doctor of Philosophy / Crashes on wet pavements are responsible for 25% of all crashes and 13.5% of fatal crashes in the US (Harwood et al. 1988). This number represents a significant portion of all crashes. Current procedures used by DOTs to identify locations with a high number of wet crashes and hydroplaning are too simple and might not represent actual risk. A fraction of all wet crashes is hydroplaning, although they are related to the difference between a "wet crash" and "hydroplaning" is a wet crash water-vehicle interaction is less compared to hydroplaning where the driver loses control. This dissertation presents a new procedure to evaluate the road network to identify locations with a high risk of wet crashes and hydroplaning. The risk estimation process uses data collected in the field to determine the risk at a particular location and, depending on the available data a transportation agency uses, will be the approach to apply. The first statistical method estimates the frequency of wet crashes at a location. This estimate is developed by using a statistical model, negative binomial regression. This model measures the frequency of dry crashes, wet crashes, traffic, and road characteristics to determine the total number of wet crashes at a location. Results indicate that this option is more reliable than the current methods used by DOTs. They divide the number of wet crashes by the number of dry crashes. Two elements identified to influence the results are the difference in road grade and its absolute value. The second statistical method to estimate wet crashes considers crash counts by applying a statistical process, spatial multiresolution analysis (SMA). Results indicate that SMA performs better than current processes based only on the crash counts. This option can identify the high-risk location for different years, called consistency. The more consistent the method is, the more accurate is the results. A third statistical method is a novel way to estimate hydroplaning risk. Hydroplaning risk is currently based on finding the maximum speed before hydroplaning occurs. A vehicle's performance related to the water-film thickness provides an estimation method developed by (Gallaway et al. 1971), which includes rainfall intensities, road characteristics, vehicle characteristics, and operating conditions. The hydroplaning risk depends on more aspects than tire inflation pressure, tire footprint area, or vehicle load on the wheel. The braking and tire tread affect the performance margin. Highway engineers can use this improved hydroplaning risk-estimation tool to analyze the road network. Finally, a critical review showed the available solutions to reduce the probability of having a wet crash or hydroplaning on wet pavement. The recommended strategies to mitigate wet crashes and hydroplaning provide information to allocate resources based on proven, practical strategies. Road geometry design can be optimized to remove water from the road. This geometry is a permanent modification of pavement characteristics to reduce water accumulation and water thickness on the road. Road surface treatments and non-engineering measures provide temporary measures to improve vehicle performance or driver operation.

Pavement structural condition plays a critical role in the rate of pavement deterioration, yet most state highway agencies' network-level decision-making processes are primarily based on surface distresses. Despite the limitations of the traditional structural condition measuring devices, some states have experimented with stationary deflection devices for network-level applications. Over the past decade, continuous deflection devices have become capable of measuring the network-level pavement structural condition information. However, since the traffic speed deflection devices use newer technology, there is a need for guidelines on how the state agencies could make use of this information for pavement management decision-making. This dissertation developed processes and enhanced tools to incorporate the pavement structural condition from the TSD into Virginia's network-level pavement management process This first part of the study developed pavement deterioration models for a subset of road networks in Virginia, to show that the pavement structural condition as measured by the TSD has an impact on the rate of deterioration of the surface condition. A structural condition matrix was then developed to augment the treatment selection process currently used by VDOT. Application of the augmented matrix on the tested Interstate network resulted in reducing the percentage of the network requiring CM and increasing the percentage requiring PM and RM. The second part of the study investigated the possibility of using pavement deflection measurements obtained from the TSD for network-level structural evaluation of pavements in Virginia. The study reported that the structural condition obtained with the TSD can replace the structural condition obtained from the FWD that is currently used in the VDOT PMS. The effective structural number (SNeff) calculated from the TSD and FWD had similar distribution, and the calculated consistency between the TSD SNeff and FWD SNeff was higher than the consistency between the SNeff from two repeated sets of FWD measurements. The third part of the study simulated the network level decision-making approaches based on both the structural condition parameter and the surface condition parameter, considering cases with and without the pavement treatment interval. The study reported that network-level decisions based on the pavement surface condition alone can result in significantly different treatment selection, compared to decisions based on the pavement structural condition. The study reported savings of 9% and 11% for cases with and without considering the pavement treatment intervals, using decision-making based on the structural condition. / Doctor of Philosophy / Pavement structural condition plays a critical role in the rate of pavement deterioration, yet most state highway agencies' network-level decision-making processes are primarily based on surface distresses. Despite the limitations of the traditional structural condition measuring devices, some states have experimented with stationary deflection devices for network-level applications. Over the past decade, continuous deflection devices have become capable of measuring the network-level pavement structural condition information. However, since the traffic speed deflection devices use newer technology, there is a need for guidelines on how the state agencies could make use of this information for pavement management decision-making. This dissertation developed processes and enhanced tools to incorporate the pavement structural condition from the TSD into Virginia's network-level pavement management process' This first part of the study developed pavement deterioration models for a subset of road networks in Virginia, to show that the pavement structural condition as measured by the TSD has an impact on the rate of deterioration of the surface condition. A structural condition matrix was then developed to augment the treatment selection process currently used by VDOT. Application of the augmented matrix on the tested Interstate network resulted in reducing the percentage of the network requiring CM and increasing the percentage requiring PM and RM. The second part of the study investigated the possibility of using pavement deflection measurements obtained from the TSD for network-level structural evaluation of pavements in Virginia. The study reported that the structural condition obtained with the TSD can replace the structural condition obtained from the FWD that is currently used in the VDOT PMS. The effective structural number (SNeff) calculated from the TSD and FWD had similar distribution, and the calculated consistency between the TSD SNeff and FWD SNeff was higher than the consistency between the SNeff from two repeated sets of FWD measurements. The third part of the study simulated the network level decision-making approaches based on both the structural condition parameter and the surface condition parameter, considering cases with and without the pavement treatment interval. The study reported that network-level decisions based on the pavement surface condition alone can result in significantly different treatment selection, compared to decisions based on the pavement structural condition. The study reported savings of 9% and 11% for cases with and without considering the pavement treatment intervals, using decision-making based on the structural condition.

During the last two decades, environmental awareness and climate change concerns have encouraged and supported the implementation of recycled techniques in the Transportation Infrastructure Industry for rehabilitating and constructing pavements in the United States. Besides that, pavement roads are public goods that bring economic and social benefits to all countries. Therefore, assessing the pavement structural condition is essential to understand the performance of new materials and determine actions for conservation, maintenance, or rehabilitation. In-situ Pavement monitoring through embedded instrumentation is a type of monitoring technique, which uses several sensors installed within the pavement to obtain the structural responses used in Mechanical-Empirical design to control the performance and define asset management plans. This thesis presents the instrumented response of a Recycled Pavement Section on the Interstate 64 (located in Virginia, USA) to analyze the actual pavement responses (strain and stress) under real traffic and environmental conditions. Several sensors were installed during the construction (including strain gauges, pressure cells, thermocouples, and TDR probes), and two recycling techniques were used (CCPR and Full Depth Reclamation (FDR)) in this project. The Instrumented Recycled Pavement Section analyzed in this research was tested during five months in 2019 to evaluate the effect of temperature, sensor location, and load configuration on the pavement responses collected in the field. During the tests, three loaded trucks ran over the instrumented section. The results showed that the pavement structure is working properly, the stress responses decreased with depth, the maximum strain over the months was compared, and the temperature effect was addressed. Nevertheless, the stress and strain data obtained in each test presented a large variability because it is difficult to control the position where the trucks are passing during this type of experiment. Furthermore, the measured strains were useful to develop a calibrated pavement structural model, which showed that the pavement is expected to have a long structural service life. / M.S. / During the last two decades, different Departments of Transportation have been studying the implementation of recycled materials in pavement structure to provide better economic, environmental, and social benefits by addressing environmental challenges within the Transportation Infrastructure Industry. Among the emerging recycled techniques, Cold-Central Plant Recycling (CCPR) and Full Depth Reclamation (FDR) are included. Both procedures recollect and use the existing asphalt in the rehabilitation or reconstruction of the new pavement structure. The main benefits of pavement recycled materials include reduction of raw materials required and gas emissions. Nevertheless, recycled techniques are not commonly implemented due to the lack of information about long-term performance under real traffic and environmental conditions. In addition, since 2004, when the new Pavement Design Guide was released, the evaluation and validation of new materials require the understanding of the interaction between material properties, traffic, and climate. To address this concern, this thesis analyzed the pavement response measurements obtained in the Interstate 64 Widening Project (Virginia, USA), where two recycling techniques were used (CCPR and FDR). In this project, several sensors were installed during the construction to obtain information regarding the current environment condition (temperature and moisture) and pavement performance (stress and strain). The recycled pavement section was tested during five months of 2019 and trucks with known load configurations were implemented in the field tests. The results showed that the pavement structure is properly working, there is an acceptable stress distribution within the pavement layers, and the overall thickness is expected to have a long structural service life. Besides that, measured strain values obtained through the field experiment were compared with the theoretical ones obtained with computational tools.

This thesis broadly addresses the issue of materials sustainability in the production of Portland cement concrete. Two methods are presented, both aimed at achieving more sustainable concrete through the use of waste and recycled materials. The first method involves utilizing reclaimed asphalt pavement (RAP) as an aggregate in structural concrete, and the second method involves utilizing waste quarry fines as partial replacement of Portland cement in concrete mixes. Many efforts have been made in recent years to justify the use of RAP aggregates in concrete. All previous efforts appear to unanimously report a reduction in concrete performance with varying proportions of RAP usage. The poor performance of RAP aggregates in concrete is attributed mainly to a larger, more porous interfacial transition zone (ITZ) and to the cohesive failure of the asphalt. It is hypothesized that the detrimental impact on the ITZ is attributable to organic compounds leached from the asphalt in the high pH pore solution. This study proves the presence of organic compounds in the pore solution and demonstrates that there is an apparent retardation of cement hydration. This study also attempted to pretreat the RAP in a sodium hydroxide (NaOH) solution to pre-leach the organic compounds. The pretreatment demonstrated that organic compounds were leached and that NaOH modified the asphalt surface chemistry. However, only a marginal improvement in compressive strength was observed by completing the pretreatment. Replacement of Portland cement by filler products is a practice aimed at reducing the carbon footprint of concrete, such as is common with Type IL Portland limestone cement. This study investigates the impact of replacing cement with seven different quarry fines materials. The quarry fines were used to replace cement at 5% to 20% by volume in either cement paste or mortar samples that were then analyzed for various physicochemical properties. It was found that all the quarry fines had detrimental impact on the hydration kinetics of cement pastes. The inclusion of quarry fines was also found to cause varying degrees of reduction in mortar compressive strength. While further analyses of the quarry fines are required, quarry fines 2, 5 and 7 did display encouraging signs to suggest the potential for use as a filler material in blended cements. / Master of Science / This thesis broadly addresses the issue of sustainability in the cement and concrete industry. Sustainability is a significant problem for the cement and concrete industry due to the large amount of carbon emissions produced in the manufacturing process of Portland cement. One method to reduce the carbon footprint of concrete is to use recycled aggregates, and reclaimed asphalt pavement (RAP) is investigated in this thesis as a recycled aggregate option. Previous studies have shown that the use of RAP in concrete results in poor mechanical performance when compared to conventional concrete. In this thesis, the RAP was pretreated by soaking it in sodium hydroxide (NaOH) to see if any improvement is noted. It was determined that the pretreatment resulted in marginal improvements in concrete performance. Another method to reduce the carbon footprint of concrete is through the use of substitutions of Portland cement. In this thesis, quarry fines from around Virginia were investigated for potential as substitutive material. Quarry fines are a by-product from quarrying operations and are often considered a waste material because they have limited applications. This study analyzed the performance of cementitious materials prepared with various substitutive percentages of quarry fines and found that, in general, the inclusion of quarry fines resulted in a decrease of mechanical performance. In total, seven quarry fines were tested and only two showed potential for use as a substitution in Portland cement concrete. These two investigations are essential in reaching the goal of reducing the carbon footprint of the cement and concrete industry.

Infrastructure systems are critical to sustaining and improving economical growth. Poor condition of infrastructure systems results in lost productivity and reduces the quality of life. Today's global economy forces governments to sustain and renew infrastructure systems already in place in order to remain competitive and productive (GAO, 2008). Therefore, civil engineers and policymakers have been quite interested in the overall quality of the highways and bridges throughout the US (Miller, 2007). Transportation networks are essential parts of the Nation's infrastructure systems. Deterioration due to age and use is the main threat to the level of service observed in surface transportation networks. Thus, highway agencies throughout the United States strive to maintain, repair and renew transportation systems already in place (Miller, 2007). A recent disaster, the collapse of the Minneapolis I-35 W Bridge, once again revealed the importance of infrastructure preservation programs and resulted in debates as to how state departments of transportation (DOTs) should and can preserve the existing infrastructure systems. Therefore, it is essential to establish effective maintenance programs to preserve aging infrastructure systems. The major challenge facing the state highway maintenance managers today is to preserve the road networks at an acceptable level of serviceability subject to the stringent yearly maintenance and rehabilitation (M&R) budgets. Maintenance managers must allocate such limited budgets among competing alternatives, which makes the situation even more challenging. Insufficient use of available smart decision-making tools impedes eliciting effective and efficient maintenance programs. Hence, this thesis presents the development and implementation of a network-level pavement maintenance optimization model which can be used by maintenance managers as a decision-making tool to address the maintenance budget allocation issue. The network-level optimization model is established with the application of the Linear Programming algorithm and is subject to budget constraints and the agencies' pavement performance goals in terms of total lane-miles in each pavement condition state. This tool is developed with Microsoft Office Excel. The tool can compute the optimal amount of investment for each pavement treatment type in a given funding period. Thus, the model enables maintenance managers in highway agencies to develop alternative network-level pavement maintenance strategies through an automated and optimized process rather than using what-if analysis. / Master of Science

Pavement macrotexture has been shown to influence a range of safety and comfort issues including wet weather friction, splash and spray, ambient and in-vehicle noise, tire wear, and rolling resistance. While devices and general guidance exist to measure macrotexture, the wide-scale collection and use of macrotexture is neither mandated nor is it typically employed in the United States. This work seeks to improve upon the methods used to calibrate, collect, pre-process, and distill macrotexture data into useful information that can be utilized by pavement managers. This is accomplished by 1. developing a methodology to evaluate and compare candidate data collection devices; 2. plans and procedures to evaluate the accuracy of high-speed network data collection devices with reference surfaces and measurements; 3. the development of a method to remove erroneous data from emerging 3-D macrotexture sensors; 4. development of a model to describe the change in macrotexture as a function of traffic; 5.finally, distillation of the final collected pavement surface profiles into parameters for the prediction of important pavement surface properties aforementioned. Various high-speed macrotexture measurement devices were shown to have good repeatability (between 0.06 to 0.09mm MPD) and interchangeability of single-spot laser dfevices was demonstrated via a limits of agreement analysis. The operational factors of speed and acceleration were shown to affect the resulting MPD of several devices and guidelines are given for vehicle speed and sensor exposure settings. Devices with single spot and line lasers were shown to reproduce reference waveforms on manufactured surfaces within predefined tolerances. A model was developed that predicts future macrotexture levels (as measured by RMS) for pavements prone to bleeding due to rich asphalt content. Finally, several previously published macrotexture parameters along with a suite of novel parameters were evaluated for their effectiveness in the prediction of wet weather friction and certain types of road noise. Many of the parameters evaluated outperformed the current metrics of MPD and RMS. / Doctor of Philosophy

This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The results showed consistent error standard deviation in the TSD measurements and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT’s Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation. / Master of Science / This thesis presents (a) some of the results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD: which is the variation in repeated TSD measurements on the same section of the road, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT). The pavement structural number is an abstract number expressing the structural strength of the pavement. The results showed that the TSD measurements were repeatable and that the TSD was able to identify pavement sections that varied in structural condition. Comparison of the SNeff calculated with TSD measurements, using an empirically developed equation by Rohde, with the SNeff calculated by PennDOT Pavement Management System based on construction history showed similar trends, although the TSD-calculated SNeff was higher. In order to develop deflection thresholds to categorize pavements in different condition: good, fair and poor, a model that related the pavement surface condition to pavement surface age and structural condition was developed. Structural condition thresholds were then selected so that the pavement surface condition predicted from the model for a 10-year-old pavement surface fell within one of the three condition categories (Good, Fair, and Poor), to identify pavements in good, fair and poor condition. With Overall Pavement Index(OPI) characterizing the surface condition and Deflection Slope Index(DSI) characterizing the structural condition, the DSI threshold that separates structurally good from structurally fair pavements was determined as follows: (1) the OPI threshold that separates pavements with good surface condition from those with fair surface condition was obtained from the Pennsylvania Pavement Management System (PMS) and (2) the DSI thresholds were calculated using the determined OPI value and the model equation.

A pavement investment and management process has a dynamic structure with cause and effect. Better investment decisions for maintenance will increase the condition of the flexible pavement and will end up with a better level of service. Therefore, better investments decisions on pavement maintenance will increase the economic growth and global competition for the area. However, improper allocation of money and resources would end up with further deteriorations of the facilities. So asset management encourages highway maintenance managers to spend their scarce budget for the maintenance that is really needed. A well-developed pavement management simulation model will allow highway maintenance managers to consider the impact of choosing one maintenance policy alternative versus another through what-if analysis and having informed decisions. Discrete event simulation (DES) is an alternative method of analysis that offers numerous benefits in pavement management. Unlike the models currently in use, a decision support model created by utilizing the DES technique would allow fractionalizing the pavement in smaller proportions and simulating the policies on these smaller segments. Thus, users would see how their decisions would affect these specific segments in the highway network over a period of time. Furthermore, DES technique would better model the multiple resource requirements and dynamic complexity of pavement maintenance processes. The purpose for this research is to create a decision support tool utilizing discrete event simulation technique where the highway maintenance managers can foresee the outcomes of their what-if scenarios on the specific segments and whole of the highway network evaluated. Thus, can be used for both project and network level decision support. The simulation can also be used as a guiding tool on when, where and why resources are needed on needs basis. This research relies on the budget allocation results from the linear optimization model (LOM). This model is a tool that creates the optimized budget allocation scheme for a network fitting to a determined scenario. Thus by integrating the LOM and the DES model, the maintenance managers can acquire an optimized budget allocation for their district and evaluate the results in both network and project selection level. Maintenance managers can obtain the best budget allocation plan without performing the repetitive trial and error approach like the previous decision support tools. There is a vast amount data in many varieties gathered as results from the simulation model. This fact alone demonstrates how powerful the discrete event simulation model is. By the nature of this simulation technique, the resources (highway segments, annual budget) can be traced throughout the simulation and this trait allows the design of the project selection level decision support system. By examining these reports, the maintenance managers can better observe how the scenarios evolve. Thus this tool helps the maintenance managers to have better decisions on the project selection level. The discrete event simulation model established in this research carries the project selection level pavement management from a position where maintenance managers should solely depend on their engineering judgment and experience to a position where maintenance managers can have more effective and justified plans since they can foresee the results of these decisions on the segments that are forming the network. This simulation engine is created with the discrete event simulation language called STROBOSCOPE. The model consists of two parts which work like a lock and key mechanism. The first part of the model is the data feeding mechanism where information from any network is loaded. The second part is the generic engine which can evaluate any road network data it is fed. The purpose of segregating these two components of the model is to allow the user to evaluate any network regardless of length, number of segments or the location. / Master of Science

Tire-pavement interaction noise is one of the dominant sources of vehicle noise, and one of the most significant sources of urban noise pollution. One critical generation mechanism of tire-pavement interaction noise is tire tread excitation. The tire tread contributes to the tire-pavement interaction noise mainly through two mechanisms: (1) tread block impact, and (2) the compression and expansion of the air in the tread groove at the contact patch. The tread pattern is the critical part of the tire design since it can be easily modified. Hence, the main focus of this study is to quantify the tread pattern contribution in total tire-pavement interaction noise. To achieve this goal, the noise produced by the tread pattern is separated from the total tire-pavement interaction noise. Since the tread pattern excitation is periodic with tire rotation, the noise produced by the tread is assumed to be related to the tire rotation. Hence, the order domain synchronous averaging method is used in this study to separate and quantify the tread pattern contribution to the total tire-pavement interaction noise. The experiment has been carried out using an On-Board-Sound-Intensity (OBSI) system. Five tires were tested including the Standard Reference Test Tire (SRTT). Compared to the conventional OBSI system, an optical sensor was added to the system to monitor the tire rotation. The once per revolution signal provided by the optical sensor is used to identify the noise signals associate to each revolution. In addition to the averaging method using optical signals, other data processing techniques have been investigated for separating the tread-pattern noise without utilizing the once per revolution signal. These techniques are autocorrelation analysis, a frequency domain filter, principal component analysis, and independent component analysis. In the tread-pattern noise generation, the tread profile is the most important input parameter. To characterize the tread profile, the tread pattern spectral content and air volume velocity spectral content for all the five tires are computed. Then, the tread pattern spectrum and the air volume velocity spectrum are both correlated with the separated tread-pattern noise by visual inspection of the spectra shape. / Master of Science

The objective of this study is to characterize the properties of typically adopted drainage layer materials in VA, OK, and ID. A series of laboratory tests have been conducted to quantify the volumetric properties, permeability and mechanical properties of the laboratory-compacted asphalt treated and cement treated permeable base specimens. The modified test protocols to determine the dynamic modulus of the drainage layer materials have been provided, which can be followed to determine the dynamic modulus of the drainage layers as level 1 input in Mechanistic-Empirical (M-E) pavement design. The measured dynamic moduli have been used to calibrate the original NCHRP 1-37A model to facilitate its application on drainage layer materials for prediction of the dynamic modulus as level 2 input. The compressive strength of the cement treated permeable base mixture of different air void contents has also been quantified in laboratory. Numerical simulations are conducted to investigate the location effects and the contribution of the drainage layer as a structural component within pavement. The optimal air void content of the drainage layer is recommended for Virginia, Oklahoma and Idaho based on the laboratory-determined permeability and the predicted pavement performances during 20-year service life. / Ph. D.