Collecting load tickets is an example of an antiquated practice that puts inspectors in harm’s way either adjacent to traffic, in close proximity to moving or backing equipment, or at times requires climbing onto trucks to reach tickets. Technology exists to collect this information electronically allowing for safer, efficient inspection methods. Departments of Transportation are charged with inspecting an increasing work load with a diminishing number of inspection staff. Recently, doing more with less has led to the prioritization of inspection activities and resulted in less collection of data and visual inspection on projects. Technology advancements are available to improve data collection and provide for more efficient inspection. Using GPS and GIS technology tied into electronic scale report-out systems, a fleet tracking system traces haul routes, reports travel time and tonnage, and even assists contractors with equipment matching and balancing. Data from this system coupled with other technologies remote monitoring of temperature, intelligent compaction, and network enabled cameras provide an opportunity to enhance inspection and increase construction inspection productivity all the while enriching detail of project records. The contribution of this paper is to provide a framework in which to combine these technologies into a multi-faceted, enhanced inspection approach.

Over recent years, organizations such as the Federal Highway Administration and Departments of Transportation across the United States have showed interest in automating highway construction processes. The addition of e-Construction and other advanced technologies can significantly improve the efficiency and safety of highway paving operations, specifically paving inspections. Activities such as collecting load tickets, tracking pavement lay-down temperatures, and monitoring roller movement are antiquated practices that DOT inspectors perform during paving operations. E-Ticketing, Paver Mounted Thermal Profiling, and Intelligent Compaction were proposed to automate paving inspections and were recently tested in two resurfacing pilot projects in the state of Kentucky. Findings from the projects indicate that the three technologies display great potential in improving safety and efficiency of paving inspections. The contribution of this thesis is to document the research effort, evaluate the effectiveness of the technologies compared to the traditional practices, and discuss the lessons learned for industry practitioners.

As-built drawings are the traditional method used by the construction industry to record changes made during construction. As-builts provide valuable information for new design projects as well as rehabilitation and remediation projects. The completeness and accuracy of these plans are essential for transportation industries and their success. While the importance of as-builts is widely recognized, the process of creating them has proven to be difficult. It is a time consuming process and entities often lack the resources necessary to complete accurate and detailed as-builts. After an investigation of current as-built operations within State Transportation Agencies, recommendations have been made to redefine construction "as-built" plans to meet current state transportation needs. First, the importance of a central storage location accessible to all stakeholders cannot be overemphasized. Along with a central storage location, standard guidelines should be developed regarding what information is required to be included within as-built plans. This study's approach to developing such guidelines included meeting with as-built end users and formulating a list of requested information. To ensure as-builts are being completed on time and accurately, it is recommended that as-built plans be developed throughout the project using simple to use editing software on iPads. A PDF editor is ideal for as-built development as PDF is the requested format by most end users. Finally, to ensure this process is being followed by construction, a liaison between as-built developers and users is recommended.

The strut-and-tie method (STM) is a simple and conservative method for designing concrete structures, especially deep beams. This method expresses complicated stress patterns as a simple truss or kinematic model made up of compression elements (struts), tension elements (ties), and the joints between elements (nodes). STM is based on lowerbound plasticity theorem, so using it properly will lead to a conservative design. Although the concepts of STM have been around in concrete design since the late 19th century, STM was first introduced in AASHTO LRFD in 1994 and ACI 318-02 in 2002. ACI 318 defines two different types of struts (prismatic and bottle-shaped) based on whether compression stress can spread transversely along the length of the strut. Recent work has brought into question whether these two types of struts do exist and whether current design provisions conservatively estimate failure loads for all members. The performance of struts and nodes were investigated experimentally by testing six fullscale concrete deep beams. The specimens had two different shapes (rectangular and trusslike), two different shear span-to-depth ratio (1 and 1.6), and three different types of development (externally unbonded bars, internally bonded hooked bars, and internally bonded bars with welded external plates). All the specimens were supported vertically and vii tested under a three-point load setup. Based on the results, the truss-like specimen failed at higher loads than rectangular specimens with the same shear span-to-depth ratio. According to these results and recent debate in the literature, bottle-shaped struts are not weaker than prismatic struts because of their shape. They are weaker due to shear failure where struts cross a diagonal tension field. Therefore, the structures should be separately checked for shear strength when they are designed with STM. In this dissertation, the development of the design equation for shear strength of discontinuity regions was introduced, and the procedure is under consideration for adoption in ACI 318-19. This research was expanded numerically by studying the effect of development type and length, strut type, and strut angle on the behavior of concrete deep beams. The crack patterns and load-displacement curves, which were obtained from experimental tests, were used to validate numerical models. The strength of concrete deep beams was assessed by modeling thirty-five specimens in a nonlinear finite element software. According to the results, development length and development types influenced the presence of tensile stress in the support nodes. Additionally, the effect of the tensile stresses from reinforcement development and diagonal tension were not additive in rectangular specimens.

The modern manufacturing marketplace is extremely complex and constantly changing. Career professionals often seek job placement, career advancement, and continuing education through professional certifications. Professional certifications in the United States (U.S.) have been evolving since 1911. In the 1950s, engineering groups established professional certifications and licenses. In the 1980s, administration of accreditation of certification programs proliferated, and by the 1990s, many government and professional organizations sought to standardize procedures for the industry. Currently, professional certifications are available for virtually every profession and issued by multitudes of organizations. Quality management (QM) encompasses an extensive combination ofprofessional abilities. Providers of professional certifications for quality management (QM) related occupations have increased as the demand for specialized employees increased. Certification can make professionals invaluable to their professions and offer substantial compensation. Return on the investment of personal development varies and requires consideration. Some non-accredited certification providers attempt to satisfy demand without conforming to consensual standards. Considering the accumulation of diverse sources professional certifications is subjective and industrial managers may consider them unnecessary, redundant of formal educations, or simply ineffective. The dispute as to how certifications arr advantageous for what industries and individuals requires continual review. This investigation attempted to identify the individual career advantages, enterprise expectations, and the range of certification programs for quality management (QM). The design of research used was a mixed-method approach to scientific inquiry. Participants from industrial professionals and certification providers participated in an online survey designed to identify certification parameters and perceptions. Survey responses were statistically analyzed using a variety of descriptive and inferential techniques. The techniques included measures of agreement, central tendency, and dispersion combined with open-ended responses to deductively and inductively formulate, analyze, and interpret a referenced conclusion. The results indicated essential parameters of professional certifications including what certifications existed, how they are implemented, acquired value ranges, perceived attributes and effectiveness, and a comparison of experienced and certified professionals.

Inadequate compaction of a soil subgrade can lead to detrimental outcomes that are not only costly but dangerous to the general public. To avoid this, quality control (QC) devices such as the nuclear density gauge (NDG) are currently being used to monitor the compaction and moisture content of soil subgrades. However, regulatory concerns associated with the NDG have encouraged federal and state agencies, as well as the heavy civil construction industry to consider non-nuclear devices for QC testing of compacted soils. One such non-nuclear device is the Soil Density Gauge (SDG), which utilizes electromagnetic wave propagation to obtain soil properties such as wet unit weight and moisture content. This research shows that through using soil-specific trend lines, the SDG has the capability of obtaining an equivalent NDG wet unit weight. Alongside the SDG, two dielectric moisture probes were also evaluated and through a calibration process on compacted soils, a general moisture content trend line was developed. This general moisture content trend line related outputted volumetric moisture contents from the moisture probes to gravimetric moisture contents. Field data were then plotted along with the general moisture content trend line to show that these devices have the potential of predicting gravimetric moisture contents. By combining the results of the SDG and moisture probe analyses, graphs were then developed that relate SDG wet unit weights to NDG dry unit weights using soil and moisture-specific trend lines.

Construction projects are complex endeavors that require the involvement of different professional disciplines in order to meet various project objectives that are often conflicting. The level of complexity and the multi-objective nature of construction projects lend themselves to collaborative design and construction such as integrated project delivery (IPD), in which relevant disciplines work together during project conception, design and construction. Traditionally, the main objectives of construction projects have been to build in the least amount of time with the lowest cost possible, thus the inherent and well-established relationship between cost and time has been the focus of many studies. The importance of being able to effectively model relationships among multiple objectives in building construction has been emphasized in a wide range of research. In general, the trade-off relationship between time and cost is well understood and there is ample research on the subject. However, despite sustainable building designs, relationships between time and environmental impact, as well as cost and environmental impact, have not been fully investigated. The objectives of this research were mainly to analyze and identify relationships of time, cost, and environmental impact, in terms of CO2 emissions, at different levels of a building: material level, component level, and building level, at the pre-use phase, including manufacturing and construction, and the relationships of life cycle cost and life cycle CO2 emissions at the usage phase. Additionally, this research aimed to develop a robust simulation-based multi-objective decision-support tool, called SimulEICon, which took construction data uncertainty into account, and was capable of incorporating life cycle assessment information to the decision-making process. The findings of this research supported the trade-off relationship between time and cost at different building levels. Moreover, the time and CO2 emissions relationship presented trade-off behavior at the pre-use phase. The results of the relationship between cost and CO2 emissions were interestingly proportional at the pre-use phase. The same pattern continually presented after the construction to the usage phase. Understanding the relationships between those objectives is a key in successfully planning and designing environmentally sustainable construction projects.

Uncertainty is a major reason of low efficiency in construction projects. Traditional approaches in dealing with uncertainty in projects focus on risk identification, mitigation, and transfer. These risk-based approaches may protect projects from identified risks. However, they cannot ensure the success of projects in environments with deep uncertainty. Hence, there is a need for a paradigm shift from risk-based to resilience-based approaches. A resilience-based approach focuses on enhancing project resilience as a capability to cope with known and unknown uncertainty. The objective of this research is to fill the knowledge gap and create the theory of resilience in the context of complex construction project systems. A simulation approach for theory development was adopted in this research. The simulation framework was developed based on theoretical elements from complex systems and network science. In the simulation framework, complex projects are conceptualized as meta-networks composed of four types of nodes: human agents, information, resources, and tasks. The impacts of uncertainty are translated into perturbations in nodes and links in project meta-networks. Accordingly, project resilience is investigated based on two components: project vulnerability (i.e., the decrease in meta-network efficiency under uncertainty) and adaptive capacity (i.e., the speed and capability to recover from uncertainty). Simulation experiments were conducted using the proposed framework and data collected from three complex commercial construction project cases. Different scenarios related to uncertainty-induced perturbations and planning strategies in the cases were evaluated through the use of Monte Carlo simulation. Three sets of theoretical constructs related to project resilience were identified from the simulation results: (1) Project vulnerability is positively correlated with exposure to uncertainty and project complexity; (2) Project resilience is positively correlated with adaptive capacity, and negatively correlated with vulnerability; (3) Different planning strategies affect project resilience either by changing the level of vulnerability or adaptive capacity. The effectiveness of a planning strategy is different in different projects. Also, there is a diminishing effect in effectiveness when adopting multiple planning strategies. The results highlighted the significance of the proposed framework in providing a better understanding of project resilience and facilitating predictive assessment and proactive management of project performance under uncertainty.

Transportation agencies face a challenging task to repair damaged roads in an aging transportation network with limited funding. In addition, the funding gap is forecasted to continue widening, which has direct impacts on the performance of surface transportation networks and the nation’s economy in the long run. Recently, transportation agencies were required by a newly enacted law to include national performance-based goals, such as environmental sustainability, in their programming and planning efforts for highway repair and rehabilitation. Therefore, the current practice in the area of highway rehabilitation planning is inadequate to handle this task and new practices are needed to improve the performance of transportation networks while maintain the national goal of maximizing environmental sustainability. Accordingly, this dissertation presents an innovative environmental-based decision-support model for planning highway construction programs. The model is developed in three main parts that are designed to: (1) model total vehicle fuel consumption and public benefits/costs of traveling on transportation networks; (2) evaluate the economic and environmental impacts of highway rehabilitation efforts; and (3) develop a multi-objective optimization model to identify and evaluate highway rehabilitation program(s) that are capable of simultaneously minimizing environmental impact and maximizing public benefits of rehabilitation decisions. First, mathematical models were developed to facilitate estimating the total vehicle fuel consumption and public benefits/cost for road users at the network-level. These models are deigned to estimate vehicle fuel consumption rate, tire depreciation cost, and vehicle repair and maintenance cost rate, in terms of major vehicle–road interaction factors, such as vehicle type, speed, and pavement conditions. The developed and statistically validated models are then used to estimate total vehicle fuel consumption and public benefits/costs at the network-level. Second, a new model was developed for evaluating the impact of decision making in highway rehabilitation efforts on greenhouse gas emissions and public travel costs. The model has the capabilities of: (1) identifying candidate rehabilitation treatment alternatives for damaged or aging pavement; (2) evaluating the impact of these treatments on pavement performance; (3) estimating network fuel consumption due to highway rehabilitation decisions; (4) estimating additional public costs as a result of travel-delay during road construction operations; and (5) evaluating the impact of rehabilitation efforts on public benefits expressed as expected savings in road user costs. Third, a multi-objective optimization model was developed to search for and identify highway rehabilitation programs that are capable of minimizing environmental impact in terms of CO2 emissions while maximizing public benefits under budget constraints. This newly developed model enables planners and decision makers to design and implement highway rehabilitation programs that are cost-effective and environmentally-conscious.

abstract: Water utilities across the United States are facing numerous challenges, such as limited funding and increasing project complexity, in constructing and upgrading their aging infrastructure. One innovative method to overcome these challenges is through the use of alternative project delivery methods (APDM), such as construction management at-risk (CMAR) and design-build (DB). Previous research has shown that APDM have the potential to deliver higher performing water infrastructure projects when compared to the traditional design-bid-build (DBB) method. However, there is a need to further examine APDM practices and develop tools that may support utilities in the delivery of their APDM water infrastructure projects. This study fills the knowledge gap by conducting several studies that may support public and private utilities in improving the delivery of their APDM water infrastructure projects. First, APDM implementation practices for water infrastructure projects are identified by assessing the state of practice, particularly during project procurement and execution. Second, DB project administration best practices are determined to support utilities seeking to add DB to their organization’s project delivery toolbox. Third, a pioneering web-based project delivery method decision-support tool was developed to aid utilities in selecting the appropriate delivery method for their water project. Finally, project-specific factors and attributes that impact project delivery performance are investigated through exploratory modeling and analysis. The study collected data on 75 completed treatment plant projects, conducted interviews with ten utilities that successfully deliver their water projects using DB, and worked closely with several industry experts through industry workshops and panels. Key findings related to water infrastructure project delivery revealed in this study included: (1) guaranteed maximum price (GMP) is the preferred compensation type for APDM projects; (2) utilities statistically having the lowest comfort level with delivering CMAR projects; (3) qualifications-based procurement is an effective DB project delivery practice; (4) the identification of 13 key project delivery method selection factors; and (5) the three highest predictors that impact unit cost performance are project complexity, project team chemistry and communication, and project size. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2020