No description available.

Finding innovative technologies for building our roads has always been of paramount importance. From moving to warm mix asphalt to decrease our indulgence in high energy consumption to substituting fly ash for asphalt binders to reduce dependence on pure asphalt binders from petroleum, engineers have painstakingly tried to develop new ways to improve the ways that flexible pavements are made. The major problem facing the next generation of civil engineers is sustainable practices on the field. Over the years, significant progress has been made in this regard on the impacts of building pavements on the environment. Characterizing these improvements tends to be difficult, and that is where Life Cycle Assessment (LCA) comes in. LCA is a technique used to analyze and quantify the environmental impacts of a product, system, or process. LCA shows where the significant impacts occur and how improvements can be made while recommending better practices. Even with its many advantages, its use is very constrained, especially in the United States, as it is still a very novel approach in design coupled with limited datasets and protocol for its operation. With modern technologies of substitute materials for binders like bio-oil from food waste, reclaimed asphalt pavement (RAP), and fly ash, there is a need to understand their environmental impacts. Furthermore, in this regard is where LCA can help using three significant areas: selection of materials, normalization, and characterization. Characterization refers to the identification and quantification of the relationships between the life cycle results and the environmental impacts. This research explores the environmental impacts of substituting other materials for asphalt binders using LCA. With variations in modifying levels of substitutes, results show promising levels in emissions of harmful gasses to both the air and water. This study explores ways used in normalizing this process as well as setting up a pathway for other asphalt binder substitutes. / Civil Engineering

A study has been conducted to compare conventional pavements and perpetual pavements with a particular emphasis on perpetual pavements. One of the main drawbacks of conventional pavements and motivations for this work is the maintenance required for hot mix asphalt (HMA) pavements with sub-drainage systems. Perpetual pavements, as the name suggests, are designed with a long life. However, this is a relatively new concept and there are still many unknowns concerning their performance. This dissertation was written to answer some of the questions. The study examines structural response and performance of perpetual pavements. Also, deterioration and performance of perpetual pavements will be contrasted to conventional pavements. Empirical data from the National Center of Asphalt Technology (NCAT) Test Track study was obtained, analyzed and used as a basis for evaluating theoretical models. Computational models for both conventional and perpetual pavements were constructed and analyzed using the general purpose finite element analysis software ABAQUS. Geometry, materials and loading are modeled with sufficient accuracy. This research examined several types of responses of perpetual pavements. It extends the traditional criteria of pavement distress by suggesting that longitudinal strain at the surface of a pavement HMA layer as an important criterion. Shear strain was studied and it provides a reasonable explanation of some distresses in pavements. By studying the FEA results from conventional and perpetual pavements and a thorough investigation of the thickness effects, it provides some rationale on why strain at the top of thick pavements is critical. The effects of dynamic wheel loadings are presented. Finally, the effect of environment, specifically temperature and moisture, on perpetual pavements are studied.

One of the vital processes for the maintenance of infrastructure is the collection of information about the inventory and current state of the infrastructure. Such activities are mostly done manually by the inspector in the field. However, Unmanned Aerial Vehicles (UAV) offer the possibilities to improving the accuracy, precision, and efficiency of those tasks. The present dissertation focusses on the evaluation of the requirements and possibilities for the incorporation of UAV in the assessment of port infrastructure, with an emphasis on pavement infrastructure. The first step to reach the goal of the research was the elaboration of an extensive literature review where the leading practices and trends for the use of Unmanned Aerial Systems (UAS) were identified. Based on the literature review, it was possible to propose a roadmap for the implementation of the UAS in the assessment of port infrastructure. The roadmap was implemented in a case study for the Norvik port in Stockholm while the restrictions and information allowed. This research produced several key findings. First, it was possible to recognize the lack of precise definitions in the pavement assessment, the faults in the current manual collection of pavement distresses and the voids in an investigation regarding the recognition of pavement defects different than cracking as some of the critical problems in the area. Additionally, the current applications like bridge and structural inspection, and available technologies like LiDAR or visual sensors were identified along with its improvement opportunities and restrictions. The key steps for the implementation of a UAS for assessing infrastructure were formulated as the identification of the needs and critical parameters, the selection of the UAS components, mainly the UAV and sensor, and the postprocessing of the data. The main conclusion drawn from the research is that it is possible to use UAS to assess the state of the infrastructure. However, not all UAS are suitable for all situations or necessities. The selection of the UA, according to the needs and limitations of the project, plays a vital role regarding the viability of implementation of a UAS for monitoring port infrastructure. The sufficiency of a UAS is closely related on its capability to acquire the information of the selected structures, with the required quality, and overcome the limitations, challenges, and restrictions of the site of application. As a way forward, the most important element to address is the implementation of Machine Learning (ML) techniques and Artificial Intelligence (AI) to extract the relevant features of the data automatically.

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Between 1890 and 1930 in the city of Indianapolis, people in charge made certain decisions regarding infrastructure—the character and condition of streets and sidewalks, the provision of sewer services and garbage collection, the location of the city’s dump, and the placement of the city’s sewage treatment plant—that resulted in long-term health and safety consequences. In Indianapolis, as in most modern American cities, some neighborhoods are less healthy for their inhabitants than others. The least healthy neighborhoods—those with the highest rates of cancer, for example—are situated on the city’s southwest side. The southwest side of Indianapolis is also the location of the landfill, the sewage treatment plant, and much heavy industry. The entire city is at the mercy of an ill-designed sewer system, a system that taxpayers are spending millions annually to repair. The years from 1890 to 1930 saw the genesis of this state of affairs. In the city of Indianapolis since 1890, infrastructure has separated people from nature and from each other on two levels: its operational level, wherein it was an objective entity that performed according to its design, and its subjective level, where it operated as a social and hygienic barrier. Streets, curbs, sewers, and sidewalks are useful and necessary elements of public health and safety. We both want and need these elements to ensure our separation from things that are dangerous, such as speeding cars and contaminated water. When government officials exercise power to declare what parts of the city street are accessible to whom, or which neighborhoods will have a wastewater treatment plant, a landfill, or heavy industry nearby, infrastructure can work to separate people.

Developments that have been taking place on Cal Poly campus over the years have altered the natural hydrology of the area. Stormwater management practices could help reduce the impacts of these developments. Computer models can help to design effective and economical stormwater management solutions at a watershed scale. As such, the objective of this study was to develop a stormwater management model for Cal Poly campus. The model was developed based on the utility data obtained from the university and other watershed data available from open sources. Field surveys were conducted to address some anomalies in the utility data, and streamflow monitoring was performed. The model was calibrated using the streamflow data measured during this study. The calibration effort significantly improved the prediction accuracy of the model. The calibrated model was then used to analyze the hydrologic performance of implementing LID systems for two projects that Cal Poly plans to build. Permeable Pavements (PPs) and Bioretention Cells (BRCs) were the LID types examined. The LIDs were evaluated based on peak flow and runoff volume reductions they would achieve. The potential reductions were compared for current conditions and the proposed project if LIDs were implemented, and for inflows to the LIDs and outflows from the LIDs. The results indicate that implementing a PP system for the proposed student apartment at the current H-1 and R-1 parking lots and a BRC system for the proposed engineering project facilities at the current H-2 parking lots will significantly reduce peak flow and runoff volume. Overall, the developed model will help the university with the traditional stormwater management practices such as flood control and to identify effective LID practices for future developments. Limitations of the current model and recommendations on how to improve the model are also discussed.

The Utah Department of Transportation (UDOT) has fully implemented the Mechanistic-Empirical Pavement Design Guide for pavement design but has been using primarily level-three design inputs obtained from correlations to aggregate base materials developed at the national level. UDOT was interested in investigating correlations between laboratory measurements of resilient modulus, California bearing ratio (CBR), and other material properties specific to base materials commonly used in Utah; therefore, a statewide testing program was needed. The objectives of this research were to 1) determine the resilient modulus of several representative aggregate base materials in Utah and 2) investigate correlations between laboratory measurements of resilient modulus, CBR, and other properties of the tested materials. Two aggregate base materials were obtained from each of the four UDOT regions. Important material properties, including particle-size distribution, soil classification, and the moisture-density relationship, were investigated for each of the sampled aggregate base materials. The CBR and resilient modulus of each aggregate base material were determined in general accordance with American Society for Testing and Materials D1883 and American Association of State Highway and Transportation Officials T 307, respectively. After all of the data were collected, several existing models were evaluated to determine if one or more of them could be used to predict the resilient modulus values measured in this research. Statistical analyses were also performed to investigate correlations between measurements of resilient modulus, CBR, and other properties of the tested aggregate base materials, mainly including aspects of the particle-size distributions and moisture-density relationships. A set of independent predictor variables was analyzed using both stepwise regression and best subset analysis to develop a model for predicting resilient modulus. After a suitable model was developed, it was analyzed to determine the sensitivity of the model coefficients to the individual data points. For the aggregate base materials tested in this research, the average resilient modulus varied from 16.0 to 25.6 ksi. Regarding the correlation between resilient modulus and CBR, the test results show that resilient modulus and CBR are not correlated for the materials tested in this research. Therefore, a new model was developed to predict the resilient modulus based on the percent passing the No. 200 sieve, particle diameter corresponding to 30 percent finer, optimum moisture content, maximum dry density (MDD), and ratio of dry density to MDD. Although the equation may not be applicable for values outside the ranges of the predictor variables used to develop it, it is expected to provide UDOT with reasonable estimates of resilient modulus values for aggregate base materials similar to those tested in this research.

While cement treatment is a proven method for improving the strength and durability of soils and aggregates, cement hydration causes shrinkage strains in the cement-treated base (CTB) that can lead to reflection cracking in asphalt surfaces. Cracking may then cause increased pavement roughness and lead to poor ride quality. The overall purpose of this research was to utilize data collected through the Long-Term Pavement Performance (LTPP) program to investigate the use and classification of CTB layers and evaluate the relative impact of cement content on the development of roughness and cracking in asphalt concrete (AC) pavements constructed using CTB layers. The data included 52 LTPP test sites, which represented 13 different states and one Canadian province, with cement contents ranging from 3.0 to 9.5 percent by weight of dry aggregate. Statistical procedures were utilized to identify the factors that were most correlated to the observed pavement performance and to develop prediction equations that transportation agencies can use to estimate the amount of roughness for a given pavement at a given age and the amount of distress associated with a particular crack severity level for a given pavement. The data collected for this study suggest that wide ranges of cement contents are used to stabilize soils within individual American Association of State Highway and Transportation Officials soil classifications. The data also suggest that CTBs comprising flexible pavement structures are constructed mainly on rural facilities. A backward-selection model development technique was used to develop sets of prediction equations for roughness and cracking. Age, AC thickness, CTB thickness, and cement content were determined to be significant predictors of International Roughness Index, while age, air freezing index, AC thickness, CTB thickness, cement content, and traffic loads in thousands of equivalent single-axle loads were determined to be significant predictors of low-severity, medium-severity, and high-severity block, fatigue, longitudinal (wheel-path and non-wheel-path), and transverse cracking in AC pavements constructed using CTB layers. Investigation of the relationships between CTB modulus and the development of roughness and cracking is recommended for further study.

Frost heave damage to roadways costs millions of dollars every year. The need for an improved understanding of the fundamental mechanisms associated with frost heave and methods for efficiently improving frost-susceptible materials prompted the Department of Civil and Environmental Engineering at Brigham Young University (BYU) to undertake a project to design, construct, and verify the functionality of a new frost heave testing apparatus. Frost heave research has been carried out for more than 75 years. The equipment used to conduct this testing has advanced in accuracy and utility over the years. To establish a background in past and current frost heave research, a survey of 12 frost heave devices, including their construction and capabilities, was performed in this research. Several design objectives were then delineated, and a nine-specimen frost heave device was designed and constructed to meet the specifications. The apparatus uses one collective heat source and one collective heat sink for all nine specimens. Heave data and temperature data are collected electronically, while the weights of the specimens before and after frost heave testing are measured manually. Preparatory tests were conducted to confirm the functionality of the data acquisition systems, the uniformity of conditions experienced by all specimens, and the replication of natural roadway freezing conditions. Once preparatory testing was complete, a full-scale frost heave test was performed using the apparatus to investigate the efficacy of cement stabilization in reducing the frost susceptibility of a Montana silt and to validate the functionality of the finished device. Results from the testing indicate that adding 2.0 percent cement actually induces frost heave in excess of that exhibited by the untreated soil. However, additions of 3.5 percent and 5.0 percent were found to be effective in preventing frost heave. Although minor, recommendations for further improvements to the frost heave apparatus include provisions to further decrease the thermal gradient across the specimen and installation of an automatic temperature control device for the water source.