A Framework for Coordinating Water Distribution System and Pavement Infrastructure M&R Based on LCCA

The disruptions the public faces daily around the world due to urban infrastructure Maintenance and Rehabilitation (M&R) activities are having significant social, economic, and environment impacts on communities. With respect to water distribution systems, there have been millions of water main breaks in the U.S. since January 2000, with an average of nearly 700 water main breaks every day. The majority of these water utilities lie under paved roads, and the Open Cut method is the most widely used technology for repairing water main breakages. Subsequently, this continually increasing pipe breakage requires the destruction of pavements that may be in good condition and thereby results in not only untimely inconveniences to stakeholders, but can have large cost implications as well. Hence, in order to reduce the impact of pipe breakage on pavements in good condition and to minimize the user disruptions, it is essential to find a way to coordinate the M&R activities for both of these infrastructure systems. Therefore, this thesis presents a framework for coordinating pavement infrastructure and water distribution system M&R activities based on life cycle cost analysis. The proposed framework considers the costs and benefits associated with each treatment in a candidate scenario. The costs of each scenario consist of the agency costs (construction and subsequent maintenance) and the user costs incurred due to work zone activities. The benefits of each scenario are measured using monetized (savings in annual maintenance costs and vehicle operation costs due to pavement treatment and pipe valuation) and nonmonetized (treatment service life) approaches. To demonstrate the framework, three scenarios (maintenance only, rehabilitation only, and a combination of both) are considered for pavement treatments, while only replacement is considered for water pipelines. The results were evaluated using the EZStrobe discrete event simulation system. Highway agencies and water utilities can use this methodology to evaluate different scenarios and enhance the robustness of their decision-making processes

Integration and Evaluation of Automated Pavement Distress Data in INDOT’s Pavement Management System

This study was in two parts. The first part established and demonstrated a framework for pavement data integration. This is critical for fulfilling QC/QA needs of INDOT’s pavement management system, because the precision of the physical location references is a prerequisite for the reliable collection and interpretation of pavement data. Such consistency is often jeopardized because the data are collected at different years, and are affected by changes in the vendor, inventory, or referencing system or reference points. This study therefore developed a “lining-up” methodology to address this issue. The applicability of the developed methodology was demonstrated using 2012-2014 data from Indiana’s highway network. The results showed that the errors in the unlined up data are significant as they mischaracterize the true pavement condition. This could lead to the reporting of unreliable information of road network condition to the decision makers, ultimately leading to inappropriate condition assessments and prescriptions. Benefits of the methodology reverberate throughout the management functions and processes associated with highway pavements in Indiana, including pavement performance modeling, optimal timing of maintenance, rehabilitation, and reconstruction (MRR), and assessment of the effectiveness of MRR treatments and schedules. The second part of the study developed correlations for the different types of pavement distresses using machine learning algorithms. That way, the severity of any one type of distress can be estimated based on known severity of other distresses at that location. The 2012-2014 data were from I-70, US-41, and US-52, and the distress types considered are cracking, rutting, faulting, and roughness. Models were developed to relate surface roughness (IRI) to pavement cracks, and between the different crack types, with resulting degrees of confidence that varied across the different crack types and road functional classes. In addition, for each functional class and for each crack type, models were built to relate crack depth to crack width. The concept can be applied to other distress types, such as spalling, bleeding, raveling, depression, shoving, stripping, potholes, and joint distresses, when appropriate data are available

Framework for Optimizing the Maintenance and Rehabilitation Schedules of Interdependent Infrastructure Systems

In current practice, civil infrastructure systems are typically managed and operated without duly accounting for the interdependencies that exist among different types of systems. Managing infrastructure systems separately may result in practices that may be cost-effective locally (for the individual system only) but not globally (for two or more systems with shared locations or functionality). This dissertation develops an optimization framework for scheduling infrastructure repairs that considers such interdependencies. The framework determines the optimal performance thresholds for applying a treatment to a primary system that is subject to disruption induced by a neighboring (secondary) system. This disruption may be deterministic or probabilistic in terms of its severity and/or the time of its occurrence. The optimization framework considers both the incremental costs and benefits of treatments applied to the primary system. A number of techniques, including first-order derivative, multiobjective genetic algorithm (NSGA-II), and sample average approximation, are presented to solve the scheduling optimization problem. The developed framework is demonstrated using two case studies involving co-located pavement and underground utility assets. In the first case study, the primary system is the pavement to be maintained using a common rehabilitation treatment (i.e., a thin hot mix asphalt overlay) that is subject to utility cuts imposed by underground utilities. The aim is to schedule the pavement treatment such that the impacts of the utility cuts are minimized. In the second case study, a water pipe is the primary system that is located beneath a pavement, and replacement of the pipe is subject to permit fees imposed by the agency managing the overlying pavement. The goal is to schedule the pipe replacement such that the pavement cut permit fees are minimized. The results obtained from the case studies show that the proposed model can provide effective maintenance schedules for a primary system in the presence of disruptions due to a secondary system

Assessing Traffic Congestion Hazard Period due to Commuters’ Home-to-Shopping Center Departures after COVID-19 Curfew Timings

In addition to a wide range of socio-economic impacts, traffic congestion during the era of the COVID-19 pandemic has been identified as a critical issue to be addressed. In urban neighborhoods, the timespan of traffic congestion hazard (HTC) after the curfew lift is subjected to the commuters’ decisions about home-to-shopping center departures. The decision for departing early or late for shopping depends on both the internal (commuter related) and external (shopping center related) factors. The present study developed a practical methodology to assess the HTC period after the curfew timings. An online questionnaire survey was conducted to appraise the commuters’ perception about departure time and to assess the impact of eight internal (family size, involvement in other activities, nature of job, education level, age, number of vehicles, number of children, and availability of personal driver) and three external (availability of shopping center of choice in near vicinity, distance to shopping center, and size of the city) factors on their decision. With an acceptable 20% response rate, Chi-square and Cramer’s V tests ascertained family size and involvement in other activities as the most significant internal factors and availability of shopping center of choice as the primary external factor. Age, number of children, and size of the city influenced to some extent the commuters’ decisions about early or delayed departure. Large associations were found for most of the factors, except education level and availability of drivers in a household. Fuzzy synthetic evaluation (FSE) first segregated the commuters’ responses over a four level-rating system: no delay (0), short delay (1), moderate delay (3), and long delay (5). Subsequently, the hierarchical bottom-up aggregation effectively determined the period of highest traffic congestion. Logical study findings revealed that most (about 65%) of the commuters depart for shopping within 15 min after the curfew lift, so HTC in the early part (the first one hour) of the no curfew period needs attention. The traffic regulatory agencies can use the proposed approach with basic socio-demographic data of an urban neighborhood’s residents to identify the HTC period and implement effective traffic management strategies accordingly

A Framework for Lane-Change Maneuvers of Connected Autonomous Vehicles in a Mixed-Traffic Environment

In the transition era towards connected autonomous vehicles (CAVs), the sharing of the roadway by CAVs and human-driven vehicles (HDVs) in a mixed-traffic stream is expected to pose safety and flow efficiency concerns even though CAVs may tend to adopt rather conservative maneuvering policies. Unfortunately, this will likely cause HDV drivers to unduly exploit such conservativeness by driving in ways that imperil safety. A context of this situation is lane-changing by the CAV, a potential major source of traffic disturbance at multi-lane highways that could impair their traffic flow efficiency. In dense, high-speed traffic conditions, it will be extremely unsafe for the CAV to change lanes without cooperation from neighboring vehicles in the traffic stream. To help address this issue, this paper developed a framework through which connected HDVs (CHDVs) could cooperate to facilitate safe and efficient lane-changing by the CAV. A numerical experiment was carried out to demonstrate the efficacy of the framework. The results indicated the CAVs’ lane-changing feasibility and the overall duration of the lane-changing if the CAV carries out that maneuver. It was observed that throughout the lane-changing process, the safety of not only the CAV but also of all neighboring vehicles, was promoted through the framework’s collision avoidance mechanism. The overall traffic flow efficiency was analyzed in terms of the ambient level of CHDV–CAV cooperation. Overall, the results of the study present evidence of how CHDV–CAV cooperation can help enhance the overall system efficiency

Sustainability Assessment of Construction Technologies for Large Pipelines on Urban Highways: Scenario Analysis using Fuzzy QFD

Urban highways users frequently face disruptions due to construction and maintenance of buried infrastructure. In conventional open cut construction, social costs (vehicle operating and traffic delay costs) are generally high at work zone construction areas (WZCA). Municipalities also bear additional costs due to early maintenance of alternate routes, i.e., non-work zone construction area (NWZCA). Besides, work zone and non-work zone areas together experience significant potential socio-economic and environment impacts. In addition to minimal disturbance to existing socioenvironmental setting and user cost savings, trenchless construction result in agency cost savings by avoiding early maintenance at NWZCA. Past studies primarily focused on social costs associated to WZCA. In present research, a sustainability assessment framework has been developed that includes agency and user costs at both the work zone and non-work zone area. The framework evaluates various traffic detoured scenarios (for open cut construction) and trenchless technology scenario based on all three dimensions of sustainability. Fuzzy Quality Function Deployment (Fuzzy QFD) method has been used to incorporate the interaction between the agency’s sustainability objectives and public expectations for large-sized pipeline construction projects in urban areas. The framework effectively handles the uncertainties associated to data limitations and vagueness in expert opinion for subjective assessment criteria. To evaluate the pragmatism of proposed framework, it was applied on the case of a storm sewer construction project in Qassim Region, Saudi Arabia. Trenchless technology was found to be the most sustainable construction scenario followed by the open cut scenario with 50% traffic detoured to NWCA. The proposed methodology is also sought to enhance decision making process pertaining to the viability of trenchless technologies in KSA and elsewhere

Performance Assessment Model for Municipal Solid Waste Management Systems: Development and Implementation

Most of the municipalities in the Gulf region are facing performance-related issues in their municipal solid waste management (MSWM) systems. They lack a deliberate inter-municipality benchmarking processes. Instead of identifying the performance gaps for their key components (e.g., personnel productivity, operational reliability, etc.) and adopt proactive measures, the municipalities primarily rely on an efficient emergency response. A novel hierarchical modeling framework, based on deductive reasoning, is developed for the performance assessment of MSWM systems. Fuzzy rule-based modeling using Simulink-MATLAB was used for performance inferencing at different levels, i.e., component, sub-components, etc. The model is capable of handling the inherent uncertainties due to limited data and an imprecise knowledge base. The model’s outcomes can exclusively assist the managers working at different levels of organizational hierarchy for effective decision-making. Performance of the key components assists the senior management in assessing the overall compliance level of performance objectives. Subsequently, operations management can home in the sub-components to acquire useful information for intra-municipality performance management. Meanwhile, individual indicators are useful for inter-municipality benchmarking. The model has been implemented on two municipalities operating in Qassim Region, Saudi Arabia. The results demonstrate the model’s pragmatism for continuous performance improvement of MSWM systems in the country and elsewhere.Applied Science, Faculty ofNon UBCEngineering, School of (Okanagan)ReviewedFacult

Life Cycle Assessment of Construction and Demolition Waste Management in Riyadh, Saudi Arabia

Extensive construction augmenting the infrastructure and real estate projects underpin Saudi Arabia’s Vision 2030 of sustainable cities. A part of this struggle involves the transformation of the existing infrastructure together with new construction, which generates a large amount of construction and demolition waste (CDW). In the absence of a structured life cycle assessment (LCA) framework, the waste management companies are planning future scenarios (phased expansions of material recovery facilities to improve the recycling rate) primarily on economic grounds. This study assesses the environmental impacts of the existing and planned CDW management practices of the Saudi Investment Recycling Company in Riyadh City by dint of LCA. Impact 2002+ performs life cycle impact assessment of the base case (45% recycling), four treatments (61, 76, 88, and 100% recycling), and zero waste scenarios. The study demonstrates the benefits of current CDW (mixed soil, concrete blocks, clay bricks, glazed tiles, and asphalt) recycling in terms of avoided impacts of non-renewable energy, global warming, carcinogens, non-carcinogens, and respiratory inorganics potentially generated by landfilling. For the treatment scenario of 100% recycling, CDW conversion into a wide range of aggregates (0–50 mm) can replace 10–100% virgin aggregates in backfilling, precast concrete manufacturing, encasements and beddings of water mains and sewers, manholes construction, non-load bearing walls, and farm-to-market roads. To achieve long-term economic and environmental sustainability, municipalities need to improve source segregation, handling, and storage practices to enhance the existing (45%) recycling rate to 100% in the next five years and approach the zero-waste scenario by 2030. The findings of the present study motivate the generators for source reduction as well as encourage the recycling companies and concerned organizations in the continuous performance improvement of the CDW management systems across Saudi Arabia on environmental grounds, as an addition to the perceived economic benefits