The consequences of failures from large-diameter water pipelines can be severe. Results can include significant property damage, damage to adjacent infrastructure such as roads and bridges resulting in transportation delays or shutdowns, adjacent structural damage to buildings resulting in loss of business, service disruption to a significant number of customers, loss of water, costly emergency repairs, and even loss of life. The American Water Works Association’s (AWWA) 2020 “State of the Water Industry” report states the top issue facing the water industry since 2016 is aging infrastructure, with the second being financing for improvements. The industry must find innovative ways to extend asset life and reduce maintenance expenditures. While are many different assets comprise the drinking water industry, pipelines are a major component and often neglected because they are typically buried. Reliability Centered Maintenance (RCM) is a process used to determine the most effective maintenance strategy for an asset, with the ultimate goal being to establish the required function of the asset with the required reliability at the lowest operations and maintenance costs. The RCM philosophy considers Preventive Maintenance, Predictive Maintenance, Condition Based Monitoring, Reactive Maintenance, and Proactive Maintenance techniques in an integrated manner to increase the probability an asset will perform its designed function throughout its design life with minimal maintenance. In addition to determining maintenance tasks, the timely performance of those tasks is crucial. If performed too late an asset may fail; if performed too early, resources that may be used better elsewhere are expended. Utility agencies can save time and money by using RCM analysis for their drinking water infrastructure. This dissertation reviews industries using RCM, discusses the benefits of an RCM analysis, and goes through a case study of an RCM at a large aqueduct in the United States. The dissertation further discusses the consequence of failure of large diameter water pipelines and proposes a regression model to help agencies determine the optimum time to perform maintenance tasks on large diameter prestressed concrete pipelines using RCM analysis.

The management of underground utilities is a complex and challenging task due to the uncertainty regarding the location of existing infrastructure. The lack of accurate information often leads to excavation-related damages, which pose a threat to public safety. In recent years, advanced underground utilities management systems have been developed to improve the safety and efficiency of excavation work. This dissertation aims to explore the potential applications of blockchain technology in the management of underground utilities and reduction of excavation-related damage. The literature review provides an overview of the current systems for managing underground infrastructure, including Underground Infrastructure Management (UIM) and 811, and highlights the benefits of advanced underground utilities management systems in enhancing safety and efficiency on construction sites. The review also examines the limitations and challenges of the existing systems and identifies the opportunities for integrating blockchain technology to improve their performance. The proposed application involves the creation of a shared database of information about the location and condition of pipes, cables, and other underground infrastructure, which can be updated in real time by authorized users such as utility companies and government agencies. The use of blockchain technology can provide an additional layer of security and transparency to the system, ensuring the reliability and accuracy of the information. Contractors and excavation companies can access this information before commencing work, reducing the risk of accidental damage to underground utilities.

The rate of urbanization has been impacted by global economic growth. A strong economy results in more people moving to already crowded urban centers to take advantage of increased employment opportunities often resulting in sprawling of the urban area. More natural land resources are being exploited to accommodate these anthropogenic activities. Subsequently, numerous natural land resources such as green areas or porous soil, which are less flood-prone and more permeable are being converted into buildings, parking lots, roads and underground utilities that are less permeable to stormwater runoff from rain events. With the diminishing of the natural landscape that can drain stormwater during a rainfall event, urban underground drainage systems are being designed and built to tackle the excess runoff resulting from urbanization. However, the construction of a drainage system is expensive and usually involves massive land excavations and tremendous environmental disturbances. The option for constructing an underground drainage system is even more difficult in dense urban environments due to the complicated underground environments, creating a need for low footprint solutions. This need has led to emerging opportunities for low impact development (LID) methods or green infrastructures, which are viewed as an environmentally friendly alternative for dealing with stormwater runoff. LID mimics the pre-development environment to retain the stormwater runoff through infiltration, retention, detention and evaporation. Despite a significant amount of prior research having been conducted to analyze the performance of runoff volume reduction and peak flow decrement of various green infrastructures, little is known about the economic benefits of using LID practices.

This dissertation fills the gap in the knowledge regarding the life-cycle-cost effectiveness of green infrastructure in current urban developments. This study’s two research objectives are:

(1) Develop a life cycle cost calculation template to analyze the cost benefits of using LID compared to the traditional drainage system

(2) Quantify the cost benefits based on the real-world construction projects

A thorough literature review led to the data collection of the hydrological benefits of using LIDs in conjunction with overviewing three real-world construction projects to quantify the cost benefits of LIDs.

Commercial buildings in the United States account for 19% of the total energy consumption annually. Commercial Building Energy Consumption Survey (CBECS), which serves as the benchmark for all the commercial buildings provides critical input for EnergyStar models. Smart energy management technologies, sensors, innovative demand response programs, and updated versions of certification programs elevate the opportunity to mitigate energy-related problems (blackouts and overproduction) and guides energy managers to optimize the consumption characteristics. With increasing advancements in technologies relying on the ‘Big Data,' codes and certification programs such as the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), and the Leadership in Energy and Environmental Design (LEED) evaluates during the pre-construction phase. It is mostly carried out with the assumed quantitative and qualitative values calculated from energy models such as Energy Plus and E-quest. However, the energy consumption analysis through Knowledge Discovery in Databases (KDD) is not commonly used by energy managers to perform complete implementation, causing the need for better energy analytic framework.

The dissertation utilizes Interval Data (ID) and establishes three different frameworks to identify electricity losses, predict electricity consumption and detect anomalies using data mining, deep learning, and mathematical models. The process of energy analytics integrates with the computational science and contributes to several objectives which are to

1. Develop a framework to identify both technical and non-technical losses using clustering and semi-supervised learning techniques.

2. Develop an integrated framework to predict electricity consumption using wavelet based data transformation model and deep learning algorithms.

3. Develop a framework to detect anomalies using ensemble empirical mode decomposition and isolation forest algorithms.

With a thorough research background, the first phase details on performing data analytics on the demand-supply database to determine the potential energy loss reduction potentials. Data preprocessing and electricity prediction framework in the second phase integrates mathematical models and deep learning algorithms to accurately predict consumption. The third phase employs data decomposition model and data mining techniques to detect the anomalies of institutional buildings.

In the United States, buildings account for 20–40% of the total energy consumption based on their operation and maintenance, which consume nearly 80% of their energy during their lifecycle. In order to reduce building energy consumption and related problems (i.e. global warming, air pollution, and energy shortages), numerous building technology programs, codes, and standards have been developed such as net-zero energy buildings, Leadership in Energy and Environmental Design (LEED), and the American Society of Heating, Refrigerating, and Air-Conditioning Engineers 90.1. However, these programs, codes, and standards are typically utilized before or during the design and construction phases. Subsequently, it is difficult to track whether buildings could still reduce energy consumption post construction. This dissertation fills the gap in knowledge of analytical methods for building energy analysis studies for LEED buildings. It also focuses on the use of green space for reducing atmospheric temperature, which contributes the most to building energy consumption. The three primary objectives of this research are to: 1) find the relationship between building energy consumption, outside atmospheric temperature, and LEED Energy and Atmosphere credits (OEP); 2) examine the use of different green space layouts for reducing the atmospheric temperature of high-rise buildings; and 3) use data mining techniques (i.e. clustering, isolation, and anomaly detection) to identify data anomalies in the energy data set and evaluate LEED Energy and Atmosphere credits based on building energy patterns. The results found that buildings with lower OEP used the highest amount of energy. LEED OEP scores tended to increase the energy saving potential of buildings, thereby reducing the need for renovation and maintenance. The results also revealed that the shade and evaporation effects of green spaces around buildings were more effective for lowering the daytime atmospheric temperature in the range of 2°C to 6.5°C. Additionally, abnormal energy consumption patterns were found in LEED buildings that used anomaly detection methodology analysis. Overall, LEED systems should be evaluated for energy performance to ensure that buildings continue to save energy after construction.

As a developing nation, China is currently faced with the challenge of providing

safe, reliable and adequate energy resources to the county's growing urban areas as well as to its expanding rural populations. To meet this demand, the country has initiated massive construction projects to expand its national energy infrastructure, particularly in the form of natural gas pipeline. The most notable of these projects is the ongoing West-East Gas Pipeline Project. This project is currently in its third phase, which will supply clean and efficient natural gas to nearly sixty million users located in the densely populated Yangtze River Delta.

Trenchless Technologies, in particular the construction method of Horizontal

Directional Drilling (HDD), have played a critical role in executing this project by

providing economical, practical and environmentally responsible ways to install buried pipeline systems. HDD has proven to be the most popular method selected to overcome challenges along the path of the pipeline, which include mountainous terrain, extensive farmland and numerous bodies of water. The Yangtze River, among other large-scale water bodies, have proven to be the most difficult obstacle for the pipeline installation as it widens and changes course numerous times along its path to the East China Sea. The purpose of this study is to examine those practices being used in China in order to compare those to those long used practices in the North American in order to understand the advantages of Chinese advancements.

Developing countries would benefit from the Chinese advancements for large-scale HDD installation. In developed areas, such as North America, studying Chinese execution may allow for new ideas to help to improve long established methods. These factors combined further solidify China's role as the global leader in trenchless technology methods and provide the opportunity for Chinese HDD contractors to contribute to the world's knowledge for best practices of the Horizontal Directional Drilling method.

Trenchless technology is a group of techniques whose utilization allows for the installation, rehabilitation, and repair of underground infrastructure with minimal excavation from the ground surface. As the built environment becomes more congested, projects are trending towards using trenchless technologies for their ability to quickly produce a quality product with minimal environmental and social costs. Pilot tube microtunneling (PTMT) is a trenchless technology where new pipelines may be installed at accurate and precise line and grade over manhole to manhole distances. The PTMT process can vary to a certain degree, but typically involves the following three phases: jacking of the pilot tube string to achieve line and grade, jacking of casing along the pilot bore and rotation of augers to excavate the borehole to a diameter slightly larger than the product pipe, and jacking of product pipe directly behind the last casing. Knowledge of the expected productivity rates and jacking forces during a PTMT installation are valuable tools that can be used for properly weighing its usefulness versus competing technologies and minimizing risks associated with PTMT. This thesis outlines the instrumentation and monitoring process used to record jacking frame hydraulic pressures from seven PTMT installations. Cyclic patterns in the data can be detected, indicating the installation of a single pipe segment, and enabling productivity rates for each PTMT phase to be determined. Furthermore, specific operations within a cycle, such as pushing a pipe or retracting the machine, can be observed, allowing for identification of the critical tasks associated with each phase. By identifying the critical tasks and developing more efficient means for their completion, PTMT productivity can be increased and costs can be reduced. Additionally, variations in depth of cover, drive length, pipe diameter, and localized ground conditions allowed for trends in jacking forces to be identified. To date, jacking force predictive models for PTMT are non-existent. Thus, jacking force data was compared to existing predictive models developed for the closely related pipe jacking and microtunneling methodologies, and the applicability of their adoption for PTMT jacking force prediction was explored.

Nowadays there is a pronounced interest in the need for sustainable and reliable infrastructure systems to address the challenges of the future infrastructure development. This dissertation presents the research associated with understanding various sustainable and reliable design alternatives for water distribution systems. Although design of water distribution networks (WDN) is a thoroughly studied area, most researchers seem to focus on developing algorithms to solve the non-linear hard kind of optimization problems associated with WDN design. Cost has been the objective in most of the previous studies with few models considering reliability as a constraint, and even fewer models accounting for the environmental impact of WDN. The research presented in this dissertation combines all these important objectives into a multi-objective optimization framework. The model used in this research is an integration of a genetic algorithm optimization tool with a water network solver, EPANET. The objectives considered for the optimization are Life Cycle Costs (LCC) and Life Cycle Carbon Dioxide (CO2) Emissions (LCE) whereby the system reliability is made a constraint. Three popularly used resilience metrics were investigated in this research for their efficiency in aiding the design of WDNs that are able to handle external natural and man-made shocks. The best performing resilience metric is incorporated into the optimization model as an additional objective. Various scenarios were developed for the design analysis in order to understand the trade-offs between different critical parameters considered in this research. An approach is proposed and illustrated to identify the most sustainable and resilient design alternatives from the solution set obtained by the model employed in this research. The model is demonstrated by using various benchmark networks that were studied previously. The size of the networks ranges from a simple 8-pipe system to a relatively large 2467-pipe one. The results from this research indicate that LCE can be reduced at a reasonable cost when a better design is chosen. Similarly, resilience could also be improved at an additional cost. The model used in this research is more suitable for water distribution networks. However, the methodology could be adapted to other infrastructure systems as well.

Trenchless technologies have emerged as a viable alternative to traditional open trench methods for installing underground pipelines and conduits. Pilot Tube Microtunneling, also referred to as the pilot tube system of microtunneling, guided auger boring, or guided boring method, is a recent addition to the family of trenchless installation methods. Pilot tube microtunneling originated in Japan and Europe, and was introduced to the United States in the year 1995 (Boschert 2007). Since then this methodology has seen increased utilization across North America particularity in municipal markets for the installation of gravity sewers. The primary reason contributing to the growth of pilot tube microtunneling is the technology's capability of installing pipes at high precision in terms of line and grade, in a wide range of ground conditions using relatively inexpensive equipment. The means and methods, applicability, capabilities and limitations of pilot tube microtunneling are well documented in published literature through many project specific case studies. However, there is little information on the macroscopic level regarding the technology and industry as a whole. With the increasing popularity of pilot tube microtunneling, there is an emerging need to address the above issues. This research effort surveyed 22 pilot tube microtunneling contractors across North America to determine the current industry state of practice with the technology. The survey examined various topics including contractor profile and experience; equipment, methods, and pipe materials utilized; and issues pertaining to project planning and construction risks associated with the pilot tube method. The findings of this research are based on a total of 450 projects completed with pilot tube microtunneling between 2006 and 2010. The respondents were diverse in terms of their experience with PTMT, ranging from two to 11 years. A majority of the respondents have traditionally provided services with other trenchless technologies. As revealed by the survey responses, PTMT projects grew by 110% between the years 2006 and 2010. It was found that almost 72% of the 450 PTMT projects completed between 2006 and 2010 by the respondents were for sanitary sewers. Installation in cobbles and boulders was rated as the highest risk by the contractors.