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Cold Central Plant Recycling (CCPR) has been used by many state highway agencies to save material, money, time, and energy in pavement construction and rehabilitation. The objectives of this thesis were to: (1) perform an instrumented verification analysis, (2) evaluate the response and performance of two pavement configurations with a CCPR base layer through accelerated pavement testing (APT), and (3) construct models using mechanistic-empirical pavement design software for comparison with the APT results. The pavement configurations featured a 5-inch CCPR mixture with either a 3-inch or 1.5-inch SM-9.5D surface mixture. Each section was instrumented with strain gauges, pressure cells, and thermocouples. A heavy vehicle simulator (HVS) was used to load three replicate test sections in each lane, with the temperature controlled at 39°C at a depth of 1.5 inches. Results from the instrument verification analysis showed that the strain gauges and pressure cells used in the experiment recorded pavement responses with a high degree of repeatability. In addition, the loading condition variables (speed, wheel load, and tire inflation pressure) affected the response following the expected trends and did not affect the repeatability of the instruments. The average CV of all strain gauge and pressure cell signals was approximately 0.009 or 0.9%, and 0.004 or 0.4%, respectively. In terms of the rutting comparison, the sections with the 3-inch surface layer outperformed the sections with the thinner 1.5-inch surface layer. However, the age of the pavement at the start of testing significantly affected the rutting performance. After adjusting for the pavement age at the time of testing, the section with the thicker surface showed approximately half of the rutting of the section with the thinner surface. The results from preliminary ME Design analysis indicate that the software cannot model the studied APT sections using the default material properties and calibration factors available at the time of analysis. In particular, the software does not seem to be prepared to model the CCPR materials. / Master of Science

One of the most important objectives for transportation engineers is to understand pavement surface properties and their positive and negative effects on the user. This can improve the design of the infrastructure, adequacy of tools, and consistency of methodologies that are essential for transportation practitioners regarding macrotexture characterization. Important pavement surface characteristics, or tire-pavement interactions, such as friction, tire-pavement noise, splash and spray, and rolling resistance, are significantly influenced by pavement macrotexture. This dissertation compares static and dynamic macrotexture measurements and proposes and enhanced method to quantify the macrotexture. Dynamic measurements performed with vehicle-mounted lasers have the advantage of measuring macrotexture at traffic speed. One drawback of these laser devices is the presence of 'spikes' in the collected data, which impact the texture measurements. The dissertation proposes two robust and innovative methods to overcome this limitation. The first method is a data-driven adaptive method that detects and removes the spikes from high-speed laser texture measurements. The method first calculates the discrete wavelet transform of the texture measurements. It then detects (at all levels) and removes the spikes from the obtained wavelet coefficients (or differences). Finally, it calculates the inverse discrete wavelet transform with the processed wavelet coefficients (without outliers) to obtain the Mean Profile Depth (MPD) from the measurements with the spikes removed. The method was validated by comparing the results with MPD measurements obtained with a Circular Texture Meter (CTMeter) that was chosen as the control device. Although this first method was able to successfully remove the spikes, it has the drawback that it depends on manual modeling of the distribution of the wavelet coefficients to correctly define an appropriate threshold. The next step of this dissertation proposes an enhanced to the spike removal methodology for macrotexture measurements taken with high-speed laser devices. This denoising methodology uses an algorithm that defines the distribution of texture measurements by using the family of Generalized Gaussian Distributions (GGD), along with the False Discovery Rate (FDR) method that controls the proportion of wrongly identified spikes among all identified spikes. The FDR control allows for an adaptive threshold selection that differentiates between valid measurements and spikes. The validation of the method showed that the MPD results obtained with denoised dynamic measurements are comparable to MPD results from the control devices. This second method is included as a crucial step in the last stage of this dissertation as explained following. The last part of the dissertation presents an enhanced macrotexture characterization index based on the Effective Area for Water Evacuation (EAWE), which: (1) Estimates the potential of the pavement to drain water and (2) Correlates better with two pavement surface properties affected by macrotexture (friction and noise) that the current MPD method. The proposed index is defined by a three-step process that: (1) removes the spikes, assuring the reliability of the texture profile data, (2) finds the enveloping profile that is necessary to delimit the area between the tire and the pavement when contact occurs, and (3) computes the EAWE. Comparisons of current (MPD) and proposed (EAWE) macrotexture characterization indices showed that the MPD overestimates the ability of the pavement for draining the surface water under a tire. / Ph. D.

Tire-pavement interaction is a dominant noise source for passenger cars and trucks above 25 mph (40 km/h) and 43 mph (70 km/h), respectively. For the same pavement, tires with different tread pattern and construction generate noise of different levels and frequencies. In the present study, forty-two different tires were tested over a range of speeds (45-65 mph, i.e., 72-105 km/h) on a non-porous asphalt pavement (a section of U.S. Route 460, both eastbound and westbound). An On-Board Sound Intensity (OBSI) system was instrumented on the test vehicle to collect the tire noise data at both the leading and trailing edge of the tire contact patch. An optical sensor recording the once-per-revolution signal of the wheel was also installed to monitor the vehicle speed and, more importantly, to provide the data needed to perform the order tracking analysis in order to break down the tire noise into two components. These two components are: the tread pattern and the non-tread pattern noise. Based on the experimental noise data collected, two artificial neural networks (ANN) were developed to predict the tread pattern (ANN1) and the non-tread pattern noise (ANN2) components, separately. The inputs of ANN1 are the coherent tread profile spectrum and the air volume velocity spectrum calculated from the digitized 3D tread pattern. The inputs of ANN2 are the tire size and tread rubber hardness. The vehicle speed is also included as input for the two ANN's. The optimized ANN's are able to predict the tire-pavement interaction noise well for different tires on the pavement tested. Another outcome of this work is the complete literature review on Tire-Pavement Interaction Noise (TPIN), as an appendix of this dissertation and covering ~1000 references, which might be the most comprehensive compilation of this topic. / PHD

El objetivo general de este proyecto es mejorar el tránsito vehicular en el casco urbano de Ciudad de Dios, distrito de San José, mediante el diseño de pavimentos y drenaje de aguas pluviales. Las malas condiciones de las calles en el área estudiada conducen a pérdidas económicas debido a que no cuentan con pavimentación y una adecuada evacuación de aguas de lluvia. Vale señalar que los residentes locales sufren problemas respiratorios debido a los desechos transportados por el aire, ante las inundaciones previstas en los últimos años por El Niño y El Niño Costero. A partir de los datos de la estación de Lambayeque, se está llevando a cabo una investigación hidrológica para establecer la precipitación máxima diaria. Para la modelización hidráulica se utilizó la versión 5.2 del SWMM (Modelo de Gestión de Aguas Pluviales de la Agencia de Protección del Medio Ambiente) de la EPA. Este es un software para la planificación de un drenaje pluvial urbano que puede diagnosticar e identificar la dirección de las aguas pluviales y obtener cálculos más precisos y optimizar el tiempo y costos. El proyecto contará con una estructura de pavimento rígido y otra de drenaje hidráulico que admita evacuar las aguas en tiempos de lluvia. Al realizar este proyecto tal cual está planteado mejorará la calidad de vida de los residentes y promoverá el crecimiento. Por ende, se llevan a cabo la búsqueda de datos preliminares, la investigación básica, el análisis de resultados, la presentación final, la observación final y para el término la sustentación del proyecto la cual son procesos claves para la aceptación y desarrollo. / The overall objective of this project is to improve vehicular traffic in the urban area of Ciudad de Dios, district of San José, through pavement design and stormwater drainage. The poor condition of the streets in the study area leads to economic losses due to the lack of paving and adequate rainwater drainage. It is worth noting that local residents suffer from respiratory problems due to airborne debris in the face of the flooding predicted in recent years by El Niño and El Niño Costero. Based on data from the Lambayeque station, a hydrological investigation is being carried out to establish the maximum daily rainfall. For the hydraulic modeling, version 5.2 of the EPA's Stormwater Management Model SWMM (Stormwater Management Model of the Environmental Protection Agency) was used. This is an urban storm drainage planning software that can diagnose and identify the direction of stormwater, obtain more accurate calculations, and optimize time and costs. The project will have a rigid pavement structure and a hydraulic drainage structure to evacuate water in times of rain. By realizing this project as planned, it will improve the quality of life of the residents and promote growth. Therefore, preliminary data research, basic research, analysis of the results, final presentation, final observation, and finally the project presentation are key processes for the acceptance and development of the project.

Road roughness is the primary source of vehicle vibrations. This thesis investigates model-based methods for estimating road roughness in terms of the International Roughness Index (IRI) by measuring the chassis vibrations of the vehicle. This can provide NIRA Dynamics AB with a cost-effective pavement monitoring solution. Initially, system identification is performed on a physical car to estimate model parameters that reflect reality. Subsequently, two model-based IRI estimation methods are developed. One method relies on a transfer function between vertical chassis vibrations and the IRI according to a quarter-car model. The second method aims first to estimate the longitudinal road profile using a Kalman filter, and then calculate the IRI values from the estimated profile. This method can be implemented computationally efficiently and also offers the possibility of estimating the IRI using lateral vibrations. Both methods are validated using real-world data, and their performance is similar when using vertical vibrations, with the IRI estimation error’s standard deviation being roughly 10% to 20% of the reference value. However, the results are considerably worse when the estimation is purely based on lateral vibrations, indicating that lateral vibrations are not feasible for model-based IRI estimation, and the reasons for this are discussed.

The need for modern transportation systems together with the high demand for sustainable pavements under applied loads have led to a great deal of research on concrete pavements worldwide. Development of finite element techniques enabled researchers to analyse the concrete pavement under a combination of axle group loadings and environmental effects. Consequently, mechanistic approaches for designing of concrete pavements were developed based on results of finite element analyses. However, unpredictable failure modes of concrete pavements associated with expensive maintenance and rehabilitation costs have led to the use of empiricalmechanistic approach in concrete pavement design. Despite progressive knowledge of concrete pavement behaviour under applied loads, concrete pavements still suffer from deterioration due to crack initiation and propagation, indicating the need for further research. Cracks can be related to fatigue of the concrete and/or erosion of materials in sub-layers. Although longitudinal, midedge and corner cracks are the most common damage modes in concrete pavements, Austroads method for concrete pavement design was developed based on traditional mid-edge bottom-up transverse cracking introduced by Packard and Tayabji (1985). Research presented in this thesis aims to address the most common fatigue related distresses in concrete pavements. It uses comprehensive finite element models and analyses to determine the structural behaviour of concrete pavements under vehicular loads and environmental effects. Results of this research are supported by laboratory tests and an experimental field test. Results of this research indicate that the induced tensile stresses within the concrete pavement are significantly affected by vehicle speed, differential temperature gradient and loss of moisture content. Subsequently, the interaction between the above mentioned factors and concrete damage modes are discussed. Typical dynamic amplifications of different axle groups are presented. A new fatigue test setup is also developed to take into consideration effects of pavement curvature on fatigue life of the concrete. Ultimately, results of the research presented in this thesis are employed to develop a new guide for designing concrete pavements with zero maintenance of fatigue damage.