Construction Research Congress 2018: Infrastructure and Facility Management

Assessing the maturity of front end engineering design (FEED) for large industrial projects is a critical task with significant influence on overall project success. The owner’s expectation is to be able to make informed decisions including cost and schedule predictions to determine whether the project should proceed to the next phase, the level of contingency needed for the project, and the predicted impact of FEED maturity on the success of follow-up phases. The primary objective of this paper focuses on FEED maturity and its impact on project performance in terms of cost change and schedule change. The authors collected data from 33 completed large industrial projects representing over $8.83 billion of total installed cost. A key result is that projects with high FEED maturity outperformed projects with low maturity by 20 percent in terms of cost growth in relation to the approved budget at Phase Gate 3.

Population aging, also known as the “silver tsunami,” has introduced changes in infrastructure needs and neighborhood development in cities. In this regard, appropriate housing and accessibility to facilities, amenities, and social services can influence seniors’ independence and quality of life. Age-restricted communities, representing a new paradigm in urban development, have become a popular option for older adults due to the many benefits they offer. This study aims to measure the regional accessibility of age-restricted communities to various facilities, including hospitals, recreation facilities, shopping centers, and parks, from resiliency and spatial perspectives. Thus, a set of methods is proposed based on a geographic information system (GIS) at the neighborhood level which involves distribution exploration of age-restricted communities, spatial analysis of facility locations by type, and gravity accessibility measures to each type of facility in a given neighborhood. These methods are then applied to age-restricted communities for independent living in Edmonton, Canada. The results of the case study indicate that different types of facilities are not equally distributed among neighborhoods, a phenomenon which is of particular concern with regard to age-restricted communities. Furthermore, since variations exist in the regional accessibility measures, seniors in these communities experience inequitable access to various facilities. Thus, suggestions and policy implementations are proposed pertaining to neighborhood design and location selection of age-restricted communities in order to improve regional accessibility.

The United States Census Bureau publishes non-residential construction spending monthly. The non-residential construction spending provides valuable information about the level of non-residential construction activities in the United States. Forecasting non-residential construction spending enables the firms that are active in the non-residential construction market to plan resources properly. However, non-residential construction spending is subject to fluctuations that makes forecasting challenging. The American Institute of Architects has introduced the architectural billing index (ABI) as the leading indicator of construction spending. The objective of this paper is to empirically examine whether ABI is helpful to forecast the fluctuations in the non-residential construction spending in the United States. Time series methods are used to achieve this objective. The results of Granger causality tests show that ABI is helpful to forecast the non-residential construction spending. It also shows ABI leads non-residential construction spending in higher lag lengths (12 months and above). Moreover, the results of cointegration tests show that there is a long-term relationship between ABI and non-residential construction spending. It is expected that this knowledge helps the construction firms to forecast non-residential construction activities that is vital for resource allocation and planning.

The paper investigates the potential reasons leading to overstock/excess/surplus stocks in inventory management of construction companies and their impacts on inventory costs. Supply chain management in itself is a value chain which involves flows of information and products through various nodes starting from procuring raw materials, manufacturing the designed products, shipping the finished products to wholesalers, distributors, retailers, installing the materials to projects. It is highly important that accurate information is maintained at each level of supply chain in terms of demand forecast to determine the amount of inventory to be kept in stock to meet the sales margins and customer service expectations. However, variability in customer consumption forces wholesalers and retailers to maintain more than required levels of inventory to address demand uncertainties. This rigor has raised the inventory levels in each business which in turn increased the capital investment into inventory that may or may not be sold in the future. In a perfect situation, where the entire inventory purchased is sold within the expected period of time, has zero or minimal loss to the business. But close to $1.4 trillion of merchandise annually has been in overstock position. Overstock in construction supply chain is also a critical issue. Overall, this research collects data from different sources to identify the factors causing surplus inventory situations and their impacts on inventory management costs in the form of capital costs, inventory costs, storage costs and risks. The research also includes a simulation model to demonstrate the cost of carrying excess inventory. Finally, the discussion deliberates how the costs of holding excess inventory can outgrow actual sales margins of inventory on hand.

The use of light detection and ranging (LiDAR) technology for slope monitoring and landslide/rockslide risk assessment on highways is proven to be one of the best practices. Registration is one of the crucial steps in data processing which involves aligning and merging of multiple point cloud datasets collected from different scan positions to obtain a complete scene. The presence of a sufficient number of planar surfaces in the data can typically improve registration results. However, due to the limited number of planar surfaces that can be extracted from the point cloud data of cut/fill slopes on highways, data registration is one of the biggest challenges for data processing. Although there exist many point cloud registration algorithms, there are no definitive guidelines for choosing the right algorithm suitable for data. This paper explains the registration procedure using the point cloud data obtained from two different landslide/rockslide potential sites on Oklahoma highways using a terrestrial LiDAR and reports technical challenges experienced during the registration process. This study presents a qualitative comparison of various registration algorithms, such as iterative close point (ICP), multi-station adjustments (MSA), and normal distribution transform (NDT). The result indicates that the most effective registration was achieved by using MSA plane patch features. These comparison results can facilitate the selection of the best registration algorithms suitable for the data and more accurate results. This paper also presents recommendations for the technical challenges experienced during the registration process.

By offering a powerful means to retrieve information from a virtual model of a facility, building information modeling (BIM) has the potential to save the costs borne by owners and operators during facility operation and maintenance (O&M). Currently, researchers and industry professionals require a state-of-the-art overview of the various BIM-related inventions and innovative applications in the facility O&M field. Through a literature review, this paper aims to evaluate and summarize current BIM-O&M research and application developments, analyze research trends, and identify promising future research directions. Publications studied in this research have shown BIM’s capabilities in providing new functionalities for facility managers and supporting them in O&M tasks. Many comprehensive systems are established on the foundation of BIM and they can efficiently acquire, store, and process information, perform analysis to inform facility managers’ decisions, and automate some of the O&M functions.

A microwave heating approach is an effective solution for curing cement-based materials because the microwave penetrates materials and efficiently distributes electromagnetic energy throughout. Furthermore, the microwave heating method contains other advantages in the way that the heating process is rapid and energy efficient and does not generate secondary wastes. To understand and estimate the performance of the microwave curing for cement-based materials, investigating an accurate numerical model is essential because the process of microwave heating is complicated, and combines two physical domains, electromagnetics, and thermal mechanics. This paper explores the significance of multi-physics simulation, which enables an accurate description of numerical models in order to better understand the microwave curing/heating process. To evaluate the heating performance of the microwave curing method, this study compared the multi-physics simulation with a model simulating a referenced traditional heating method. The simulation results indicated that the proposed microwave heating approach was more effective in curing concrete than the conventional heating approach. A multi-physics simulation approach as well as the findings of this study could benefit the construction industry by facilitating the process of concrete curing by means of precise electronic control of cleaning heating.

Recent advances in data and information technologies have enabled extensive digital datasets to be available to decision makers throughout the life cycle of a transportation project. However, most of these data are not yet fully reused due to the challenging and time-consuming process of extracting the desired data for a specific purpose. Digital datasets are presented only in computer-readable formats and they are mostly complicated. Extracting data from complex and large data sources is significantly time-consuming and requires considerable expertise. Thus, there is a need for a user-friendly data exploration framework that allows users to present their data interests in human language. To fulfill that demand, this study employs natural language processing (NLP) techniques to develop a natural language interface (NLI) which can understand users’ intent and automatically convert their inputs in the human language into formal queries. This paper presents the results of an important task of the development of such a NLI that is to establish a method for classifying the tokens of an ad-hoc query in accordance with their semantic contribution to the corresponding formal query. The method was validated on a small test set of 30 plain English questions manually annotated by an expert. The result shows an impressive accuracy of over 95%. The token classification presented in this paper is expected to provide a fundamental means for developing an effective NLI to transportation asset databases.

The transformation of the construction industry from 2D drawings to 3D models was a big revolution enhanced by the advent of building information modeling (BIM). The next progression to achieving the full potential of 3D planning models is to apply BIM and associated augmented reality (AR) systems, specifically for the needs of the underground utility industry. An example is the use of BIM and AR to map, detect, and visualize objects that are not visible to construction personnel. This paper identifies and discusses the various challenges of applying AR in the underground utility construction industry through a review of over 500 publications from 2006 to present and a Meta-analysis of the data. The challenges and barriers are categorized into: (1) data collection issues; (2) modeling alignment barriers; (3) hardware limitations; and (4) data storing and managing challenges. The main associated issues are discussed and further recommendations to overcome these challenges are presented. This paper provides a contribution by showing underground project stakeholders the barriers to overcome in applying AR. The main motivation of this research is to make the construction industry aware of the benefits of leveraging AR to prevent utility strikes, while enhancing productivity.

In the present era of data analytics, industries leverage the power embedded in the abundant data generated rapidly to improve procedures and facilitate decision making. The architectural, engineering, construction, and facility management (AEC/FM) industry as well, begins to realize the benefits of data-driven approaches. However, AEC/FM is still behind many other industries in leveraging the advantages of data. During the last decade, researchers have focused their attention to emerging construction trends such as building information modeling (BIM). Integrated with data analytics, such trends have high potential to continue the technology evolution of the industry. This paper consolidates the records of current relevant efforts in AEC/FM academic research and evaluates the conclusions from this literature exploration through an industry survey. Following a comprehensive literature review, a three dimensional evidenced taxonomy was developed by categorizing the primary concepts into related segments that maps: (1) data analytics concepts such as cloud computing and machine learning, onto (2) AEC/FM emerging trends such as BIM and automation, and (3) existing and potential AEC/FM applications such as safety and progress monitoring. The same categorization was used to conduct the survey. Statistical analysis of the survey results indicates a general agreement between the literature-based identified technology trends and application areas that can benefit from data. BIM exhibited the most promising Technology Trend when integrated with data analytics in both literature and industry surveys. As for the application areas, process efficiency and productivity improvement ranked the highest in the literature and industry survey, respectively. This study contributes to the body of knowledge and practice by creating an evidenced account of the existing frameworks that benefit from data analytics and future potentials from both the academic and industry standpoints.

Industrialized construction (IC) is the process of producing prefabricated systems, building components, or building structures in a protected factory environment and transporting them to the construction site for installation or assembly. The IC process engages an enormous amount of information from different sectors of industry, including design, supply networks and materials management, planning and scheduling, and fabrication/manufacturing. While manufacturing and automation studies are commonplace in many sectors, the construction industry remains one of the least industrialized sectors. IC has emerged as a viable solution for most historical problems that the construction industry has faced. The purpose of this paper is to review the state-of-the-art of information management systems applied to IC in order to identify challenges and problems for further studies. Systematic search and screening procedures were used to identify relevant publications using major databases, including EBSCO host, ScienceDirect, Web of Science, ASCE, Emerald, and ProQuest. Challenges and problems of the selected articles were classified in the four main areas of “design and planning,” “fabrication,” “supply chain management,” and “setting and assembly.” This study reveals that while technologies are evolving, there is still a gap in the application of technologies and measurement of their benefits.

The indoor localization function is essential for facility management, especially on facility maintenance management (FMM). Meanwhile, FMM can benefit from building information modeling (BIM), which can provide rich geometric and semantic information. Therefore, the integration of real-time location information and BIM can provide more efficient facility management approaches. This paper presents a location aware BIM system that can simultaneously provide customized facility information obtained from BIM and user’s location information to achieve more efficient and intelligent facility management. The developed system firstly extracts required facility information from BIM models using BIM software API. Then, a location aware function is enabled based on the wi-fi fingerprinting technique and the previously extracted information. Lastly, a mobile application is developed to enable facility management staff to obtain the current location and to access required facility information. In addition, the developed system is tested in the HKUST library, which illustrates the efficiency of the developed location aware BIM system.

As technology developed, the architecture, construction, and engineering (AEC) industry was introduced to high-performance materials, integrated building systems, and comprehensive processes to improve the performance quality of the built environment. As a consequence of that improved performance, the design phase of the building life-cycle became more complex and comprehensive with all the engineering analyses. To aid this process, many engineering analysis and simulation programs were designed. However, with the increase in all the various software, interoperability problems emerged during the information exchange process, which also decreased the efficiency of the design and construction phase. This paper includes the first step of interoperable prototype development for a three-step analysis. In the light of literature review, researchers identified a critical and scalable geotechnical problem that is studied on a use case in central Illinois. Geotechnical engineering analysis is found to be suitable to solve the limitations of interoperability between geotechnical data and building information modeling (BIM) efforts in construction. This research contributes to the body of knowledge by developing the basis of a geotechnical information model which creates through visualized soil boring logs. This virtual database is aimed to be used for calculation of soil volume, selection of excavation equipment based on cost and schedule information which is critical for excavation processes.

Over the years, PPPs in the USA have used different types of payments to compensate project developers. In the past decades, the dominant type was toll payment. Availability payments started to gain more popularity with performance-based PPP contracts. Internationally, some other payment types are also used in PPPs, such as operation and maintenance payment, safety payment, satisfaction payment, and end of term payment. A payment mechanism is a package that includes a set of payment type(s), performance measures, performance specifications, and penalties for not meeting the specifications. Since PPP payment mechanisms, other than toll payments, is new in the USA, it is not clear whether payment mechanisms as used in the USA projects would be similar to those used in the PPP international market regarding the payment types, payment structure, performance measures and specifications, penalties, and deduction schemes. This research investigated the payment mechanisms in transportation PPP projects in the USA and Canada. Comparative and content analyses of project agreements are used as research methods. The findings show that PPP projects in the USA tend to have payment mechanisms of fewer payment types, less sophisticated payment calculations, and less complex deduction schemes. Public agencies would use the outcome of this research to revisit and improve the design of payment mechanisms of their PPP projects.

Design build (DB) is one of the most widely used alternative project delivery methods for constructing buildings and infrastructure projects in the U.S. According to a market intelligence study by RSMeans, 40% of nonresidential construction projects used the DB method in 2013. The use of DB in infrastructure and building projects has increased about twofold in the last decade. Various studies have compared project performance between DB projects and traditional design bid build (DBB) projects, and most showed that a cost as well as schedule advantage were the major benefits of DB compared to DBB. However, until now, no studies have been conducted to determine the differences in performance among DB projects or to compare cost growth with schedule growth in these projects. These were the focus of this study. Data from 26 highway and 31 building DB projects were collected, and the cost and schedule growth were compared to determine cost and time effectiveness. The results showed that there was no significant difference between the cost and schedule growth in highway and building projects. When schedule advantage was compared to cost advantage in these types of projects, it was found that owners were receiving significantly higher schedule advantage compared to cost advantage. This finding shows that DB delivery method should be used to save time rather than to save money.

Some examples of factors leading to cost and schedule overruns in a project are design changes; material, labor, and equipment shortages; location restrictions; and unpredictable weather conditions. Proper planning and control of a project could minimize these factors but will not be able to eliminate them. Some factors related to project procurement—e.g., types of delivery method, numbers of bidders, and contract types—have been found to have a relationship with the cost and schedule growth of a project during the construction phase. Therefore, it is necessary to determine whether project procurement factors could be used to predict the construction cost and schedule growth of the project. This study collected data from about 129 completed highway projects from the Texas Department of Transportation. Multiple linear regressions were performed to develop regression equations for cost and schedule growth based on six procurement factors, which were the number of bidders, the percentage difference between the award and estimated cost, liquidated damage rate per day, contractor residency, funding types, and project locations. Out of data for 129 projects, 100 were used to develop multiple linear regression equations and 29 were used to validate the regression models. The multiple linear regression showed that cost growth significantly decreased when out-of-state contractors got involved in the projects. However, schedule growth increased when the number of bidders and the difference between the award cost and engineers’ estimate increased. Using these linear regression equations, the validation of these models showed that for most of the projects, values were predicted within +/- 20% of the actual values. The findings of this research are based on Texas highway projects, so it cannot be generalized to other states.

Disputes are common in the construction industry and lead to unnecessary costs and schedule overruns in projects. While many believe that project stakeholders’ early involvement in projects impact performance metrics such as the frequency and severity of disputes over a project, no previous study has empirically tested this hypothesis. Therefore, this study empirically tested the following two null hypotheses as they relate to public highway projects: (1) project stakeholders’ time-of-involvement in the pre-design, conceptual design, schematic design, design development, construction document, and bidding phases do not yield significant differences in project performance metrics; and (2) there are no significant differences in project performance metrics between projects that feature project stakeholders’ involvement before the project bidding and those that involve project stakeholders after bidding. To test these hypotheses, this study developed and distributed a survey instrument to procurement personnel in state departments of transportation (DOTs) across the United States. Data on 60 projects from 22 DOTs were received. The data obtained were analyzed to find any statistically significant difference between dispute frequency and severity, relevant performance metrics, and the time-of-involvement of project stakeholders (such as contractors and subcontractors). The general trend in most project dispute performance metrics indicated that as the time-of-involvement moved from the pre-design to the bidding phase, the frequency and severity of disputes increased. While the differences between construction satisfaction and overall success were minor, projects in which stakeholders were involved earlier in the project had lower schedule and cost growth and significantly different design satisfaction level. The findings of this study contribute to theory by expanding knowledge about the role of early involvement of contractors and subcontractors on projects’ performance. Concurrently, the results provide empirical evidence for decision makers in DOTs to make better-informed decisions regarding the selection of projects’ organization.

Selecting the best-fit project delivery method (PDM) remains challenging for utility companies. These issues stem from the unique features and requirements of utility construction, including complex installation work, the need for strong coordination between construction and operation, and long lead times for customized materials and equipment. While previous studies established the knowledge base on the selection of PDM in building and transportation projects, the applicability and effectiveness of such best practices in the utility industry remain unknown. This paper presents a framework for utility companies to select the best-fit PDM. This framework is based on the review and comparison of existing practices and special requirements in the utility construction. In particular, a case study on a distribution substation in Maryland will be discussed and evaluated. Three predetermined delivery methods—engineering procurement and construction (EPC), engineering procurement and construction management (EPCM), and work package structure (WPS)—are examined and discussed in relation to the eight criteria under the PDM selection framework.

Construction project teams are increasingly embracing supply chain integration practices (SCIPs) for complex projects. These SCIPs utilize formal or informal mechanisms that allow multiple actors and firms to collaborate together for the overall benefit of the project. This paper looks at the joint impact of four of these SCIPs—early involvement of key stakeholders, co-located project teams, multi-party contracts, and the last planner system (LPS)—on construction speed performance. As the use of SCIPs has emerged on construction projects, the interactive complexity between different practices poses challenges for qualitative and quantitative researchers. This paper pilots the use of fuzzy set qualitative comparative analysis as a middle ground approach to study SCIPs for construction schedule performance. The pilot analyzes nine case studies from California healthcare projects completed between 2010 and 2018. The resulting preliminary findings provide evidence that improved construction speed performance requires colocation—a necessary condition—combined with either early involvement of trade contractors or combined with incentivized multi-party contracts and the LPS. The calibration and conditioning system used for SCIPs in this pilot can be expanded to additional projects and/or to additional outcomes of interest for future research.

Contracting methods for commercial construction projects utilizing an integrated project delivery (IPD) method vary based on experience, company culture, and sophistication of project participants. This research compares and contrasts contracting methods across two concurrent hospital construction projects in Colorado’s Denver metro region. One facility had a project value of roughly $160 million. The second had a project value of roughly $110 million. This research compares pre-construction data as well as findings from a short survey of project participants to analyze differences in contracting methods and outcomes. Several of the contractors and designers surveyed worked on one or more projects resulting in reliable direct comparison analysis. Metrics for comparison include: average time to negotiate and implement the project-unique contracts, impacts on profit, and design/construction productivity. Preliminary findings suggest that differences in contracting methodology and types of contracts used primarily impacts relationships, but also has possible impacts on pre-construction productivity.

The timely and coordinated functioning of critical infrastructure enables healthcare facilities to efficiently provide patients with proper care during post-disaster recovery. Specifically, to efficiently treat patients in a post-disaster situation, hospitals require sufficient medical staff, beds, medical supplies, water and electricity for treatment and building facilities, and auxiliary capacities (i.e., bottled water and backup generators) in preparation for utility disruption. Any disruption to the related infrastructure may impair the quality of patients’ medical treatment. As it is not economically viable to have substantial resources reserved in case of utility disruption, healthcare facilities need to prepare strategic medical processes to adequately serve patients under utility service constraints. This research utilizes the theory of intelligent planning units (IPUs), which enhance post-disaster robustness of healthcare systems by streamlining the process for post-disaster operation. The IPUs were designed by breaking down the post-disaster operation of healthcare systems into process units at a single-patient-care level while the IPUs scale up to plan the process at a higher level (e.g., service-room-level or hospital-level). To demonstrate their application, this study explored the process of a hypothetical intensive care unit under varying conditions of utility availability. The outcome of this research is well-defined process IPUs for single-patient-care that can be replicated to optimize the process at a higher level of medical operations during ex-ante post-disaster scenarios. Further, the unavailability of utility services governs the feasible quality of medical treatment processes. This study offers guidance on how to plan auxiliary capacities to support optimal medical treatment processes in various post-disaster scenarios.

Cities around the globe are using trip planning platforms to develop more resilient transportation networks. However, these platforms are often constrained by the missing capability of multi-modal planning, the lack of high-quality open data, and the high cost of premium APIs. They are also often not ready for large-scale calculations and analyses due to the constraints of the computing resources or the rate limits placed by commercial APIs. In this paper, we present an open platform called “transportation network resilience analytics (TNRA)” platform. Building on the mature and acclaimed OpenTripPlanner routing engine, the platform automates the process of obtaining and importing OpenStreetMap (OSM) and general transit feed specification (GTFS) data for multi-modal trip planning. TNRA also includes multiprocessing and cluster computing capabilities to enable parallel computing for large-scale calculations and analyses across multiple machines. To validate the platform, we compared the calculations between TNRA and Google Maps. We also conducted a case study in Boston to demonstrate the potential usage of the platform. The TNRA platform calculated the normative accessibility of neighborhoods in Boston’s evacuation zones to the designated shelters during a simulated strike of a hurricane. The comparison and case study confirm the validity of the platform and demonstrate its potential applications.

Participation in post-disaster shelter reconstruction is recognized as an important factor for supporting the sustainability and resiliency of the built environment. Engaging communities in the reconstruction process can help build community capacity and lead to sustained success of recovery projects. However, existing practice often assumes that differing forms of participation are independent of one another, neglecting to understand the influence that early participation may have on participation in later stages of the project. Past literature identified how communities participated in the planning, design, and construction phases in 19 different shelter projects following Typhoon Haiyan in the Philippines. For this research, we used fuzzy-set qualitative comparative analysis (fsQCA) to analyze how participation in earlier phases of planning and design affected participation in the construction phase. Results show that early participation, particularly in the decisions of the planning phase, are critical in shaping later participation. Findings also reveal that participation is a process linked across multiple project phases and should not be viewed as a set of independent tasks. These results inform disaster recovery practice by encouraging project strategies that incorporate community participation from the beginning through the end of a project’s lifecycle.

As sovereign nations, tribes have unique legal and regulatory status in the United States, which effects the procedural framework that construction takes place within. The increasing complexity of construction projects creates the need for innovative delivery systems within tribal nations. This paper presents results of an interview-based study that sought to understand what makes construction on tribal lands “different”? The authors conducted this study to identify best practices for construction within tribal nations. The authors leveraged qualitative research methods to explore the viewpoints and distinct experiences of professionals, tribal and non-tribal, working on construction projects within tribal nations. The authors recruited interviewees at tribal conferences, and ended up interviewing 22 practitioners in Arizona, including planners, architects, contractors, and owner’s representatives. The interview comprised 11 questions regarding the interviewee’s construction experiences on sovereign tribal lands. Results of this study revealed 10 unique features of construction projects within tribal nations, ranging from unique land ownership agreements to diverse architectural expectations within the community. These features represent critical planning issues that must be explored and addressed prior to beginning construction projects in tribal nations. This paper concludes with suggestions for future work and explores themes related to developing a planning process for tribal projects.

One of the enablers of organizational resilience is inclusiveness. Inclusiveness is the process of valuing, respecting and supporting members of an entity. Resilience in permanent organizations can be defined as the capability to respond to and prepare for disruption and thus, promote business continuity. On the other hand, resilience in temporary multidisciplinary organizations (TMO) can be defined as the capability to respond to, prepare for and reduce the impact of disruptions caused by the drifting environment and complexity. A construction project can be viewed as a TMO. The time-limit and contract-focus of TMO challenges inclusiveness and hence makes its impact on resilience in TMO, unclear. Given the dynamic nature of TMOs (highly susceptible to disruptions), there is the need to identify the impact of inclusiveness, thus, the aim of this research. Using a case study approach (two case studies) and critical incident technique, it was identified that the TMO in which inclusiveness was actively promoted responded better to disruptions. This was enabled by project managers, directors and the project execution plan. The identified impact of inclusiveness in managing disruptions were; time and cost savings, innovation and quality enhancement. These findings contribute to debates on disruption management in TMOs (projects).

Developing countries usually seek external aid as these countries usually struggle to solve their challenges from within and through their own resources. One solution that their governments could adopt is endorsing successful business models to develop educational and security initiatives within the jurisdiction of their own neighborhoods. This will lead to measurable increases in literacy, employment and quality of life. This paper provides corporate social responsibility (CSR) initiatives within a real estate development (RSD) corporation in Egypt that focuses on two dimensions, first the development of an educational pedagogy that helps curbing illiteracy levels, and second, an effort to develop an infrastructure system in deprived districts. The study was based on interviewing 150 construction professionals and 300 deprived families. Implementing an adaptive management approach to this resilient initiative resulted in 6% increase in literacy and reduction in illiteracy rates within families through offering education to underprivileged classes, 4% growth in employment by increasing the number of employment opportunities within the construction industry, 10% improvement in the infrastructure within the province of the RSD, by either extending/connecting sewage, water or electrical lines, and 28% reduction in crime rate, by bridging social gaps within the Egyptian society. The outcomes suggest that CSR initiatives driven by RSD are a proof of concept that yields to resiliency in the social and economic sustainability especially in the third world countries, which are plagued with underprivileged communities.

Value engineering (VE) can be a very valuable tool in the field of civil engineering and the construction industry. VE has tremendous benefits in both cost-saving and project improvement areas. Between the pay-offs and wide variety of applications, it is unsurprising that more firms are adopting the principles of VE in the design and construction phases of their projects. Many studies have been conducted on the invention of new tools for VE while others focused on the application aspect of VE in different engineering domains. This paper presents an overview of VE and its applications in the field of civil engineering. The study should prove useful for future researchers who wish to update their knowledge with the latest status of the state of art of VE application in civil engineering.

Increasingly, the public is mandating better accountability of municipal resources as evidenced by the growing demand for higher levels of service and longer asset life spans. However, municipalities are custodians of vast inventories of public assets that are worth millions (or sometimes billions) of dollars, which include land, buildings, equipment, water and sewage treatment plants, parks, roads, utilities, and bridges. The aim of the study discussed in this paper is to review and summarize the asset types and classifications that exist in North American municipalities. The study also addresses the need for appropriate asset condition assessment and risk management. The paper then presents a case study that uses a geographic information system (GIS) approach for managing these asset types and classifications. The results suggest that properly identifying and classifying assets are necessary for the effective management of municipality assets. Furthermore, using GIS in asset management contributes to the effectiveness of maintenance decisions by providing automated means for delivering quality condition data in a timely manner.

Corrosion of reinforcement due to chloride-ion contamination in reinforced concrete (RC) bridge structures is one of the major deterioration distresses in highway bridges of the United States. The deterioration process starts with minor cracks and spalls, causing loss of concrete cover. The process continues to cause damage to large surface areas along with significant loss in reinforcement, causing structural distresses. To preserve and correct RC bridge structures constructed in a chloride-laden environment, a series of maintenance, repair, and rehabilitation (MR&R) works could be performed. This study investigated chloride-induced corrosion damage as well as the maintenance practices regarding the reinforced-concrete bridge-pier columns. A questionnaire survey was conducted with 50 state departments of transportation (DOTs) to collect (1) preventive maintenance and corrective maintenance practices; and (2) information related to the durability and effectiveness of the repairs. Additionally, the study investigated the effectiveness of using externally bonded fiber-reinforced-polymer (FRP) composites in corrosion repair of bridge-pier columns, an approach widely practiced among the departments of transportation. This paper presents the profile to obtain a corrosion-damage using repair criteria for pier columns exposed to various environmental conditions. This profile could be useful for life-cycle cost analysis of maintenance and repair activities.

Transportation agencies routinely sponsor research whose findings are written into research reports and disseminated predominantly through presentations, journals, conferences proceedings, and guidebooks. Over the last few years, guidebooks have become increasingly popular among agencies, such as the American Association of State Highway and Transportation Officials (AASHTO), due to the fact that guides provide a way for practitioners to read and implement research results without including all the research background that supports the findings, but could distract the reader from the results. Guidebooks often include references to the research reports, which are of assistance for practitioners that are interested in the research background. Well-written guidebooks allow practitioners to implement the research findings effectively. However, there is a need to assess the quality of guidebooks to determine if they convey the message in a manner that is understood and can be implemented by practitioners with little or no training. The authors of this paper received research support to write an AASHTO guidebook on construction partnering. A vetting workshop was conducted with a state department of transportation (DOT) to assess the quality of the guidebook and its readiness for implementation. Vetting is a process of evaluating the quality of the dissemination instrument taking into consideration qualitative measures. This paper outlines the framework that was used for vetting the guidebook and presents the results of the vetting workshop. Based on the results of the workshop, the research team was able to revise and improve the partnering guidebook, which led to a better product.

Bridges play a vital role in resolving transportation problems in Egypt. The objective of this research is to predict the conditions of bridges expansion joints (EJ), with the aim of proposing appropriate maintenance and repair strategies that extends their lifespans. An expansion joint management system (EJMS) was developed with the aim of recommending the optimum maintenance strategy for bridges that optimizes time and cost. This model uses a combination of fuzzy logic (FL) and genetic algorithm (GA) in order to provide optimal recommendations. Moreover, a transition matrix for predicting deterioration of EJs using Markov Chain was developed. In order to test the model, several case studies of existing bridges in Egypt were used and the results were assessed against those documented through visual inspection. The comparison indicated that the developed EJMS is efficient in predicting the bridge EJs condition, where there was a deviation of 5% between the predicted condition from EJMS and the actual conditions observed through visual inspections. In addition, EJMS can play an important role in supporting decision makers in selecting the optimum maintenance and repair strategy that would minimize the overall condition of expansion joints while meeting a certain budget constraint.

In the utility infrastructure domain, utility-specific knowledge is represented in heterogeneous formats, for instance, in text-based documents and GIS-based systems. The heterogeneity of utility knowledge representation causes data interoperability issues and thus hinders data and information communication in the utility infrastructure management process. This paper presents an ontology-based approach to representing knowledge in the utility domain. The ontological model is created by investigating the utility specifications and extracting the domain knowledge. It summarizes the most fundamental concepts in the domain in a structured, extendable, and flexible format to facilitate future evolution and extension. Also included in the ontology is the formal and explicit specification of a shared conceptualization of the spatial relations used in utility industry, which are critical to the design, construction, and compliance checking of utilities.

Emerging information and communication technologies like building information modeling, internet of things, social networking, cloud computing, big data analytics, mobile application and so on serve as important catalysts to transform the practices of infrastructure asset management (IAM). Owners, occupiers, managers, operators and contractors of infrastructure facilities can now capture, process, share, integrate, and analyze data related to various infrastructure facilities collaboratively and cooperatively to achieve an integrated whole life cycle IAM. This should help improve the overall efficiency of a community and/or city through optimized resource allocation; reduced maintenance and refurbishment cost; less energy consumption; lower risks of service disruption; increased transparency; and better strategic, tactical and operational decisions. This paper outlines the development of a social networking enabled crowdsourcing system for integrated IAM. The system is designed to satisfy the requirements of different stakeholders in managing, operating and repairing a series of interdependent infrastructure facilities. Preliminary studies on the residential sector of Hong Kong reveal that the system could help improve the communication between stakeholders, enhance the transparency and effectiveness of asset management, and reduce the risks of bid-rigging in the repair and maintenance schemes. By integrating the proposed system with the existing systems being adopted throughout the entire building life cycle, such as the building information modeling and asset management systems, facility condition, and usage data that is difficult to obtain through traditional means can now be crowdsourced, co-created, or co-processed for facility performance analysis, complaint analysis, and service scheduling analysis.

Construction enterprises, which is a major constituent of the private sector, have strong construction and financing capacities in PPP projects. However, the operation inefficiency of construction enterprises greatly hinders the successful implementation of PPP projects. A proper participation mode selection mechanism of construction enterprises in PPP projects which takes their operation abilities into consideration is quite necessary. Therefore, this study aims to: (1) investigate the three typical participation modes of construction enterprises in PPP projects; (2) develop the benefit distribution models for different participation modes using the Shapley value method and modified the models based on critical factors influencing the benefit distribution of PPP projects; (3) validate the developed models through a case study. In order to achieve the objectives, this study first deduced that the separated build and operate (B&O), B&O joint venture, and combined B&O were three typical participation modes. Moreover, this study developed and modified the benefit distribution models for different participation modes and by considering the critical factors influencing the benefit distribution such as the risk and investment. In addition, the case study validated that the developed models are effective. This study first contributes to the body of knowledge on the participation mode selection of construction enterprises in PPP projects and the corresponding benefit distribution under each mode. Finally, this study provided suggestions on the rational selection of the participation mode for construction enterprises in PPP projects. Meanwhile, the findings can help the construction enterprises make proper decisions on the participation mode in PPP projects in practice.

To date, understanding and balancing the iron triangle (traditional three-dimensional project management theory) has been perceived as fundamental project management. However, previous studies have shown that large complex transportation infrastructure projects continually suffer from poor performance in terms of cost, schedule, and deliverables. Recent studies have shown that the current project management body of knowledge (traditional three-dimensional project management theory) may not be adequate to address interrelated and dependent variables encountered on complex civil infrastructure projects. Recent empirical evidence suggests the presence of five dimensions of complex civil infrastructure projects: cost, schedule, technical, context (externalities), and financing that need to be effectively managed on complex civil infrastructure projects. For successful transportation project management, there is a critical need to understand the complex civil infrastructure projects and identify interrelationships among the five dimensions. The aim of this paper is to present a comprehensive review of the literature on complex projects, complexity theories, and five dimensions. This paper provides useful insights into the importance of the understanding the complex civil infrastructure projects, summaries from published literatures on five dimensions and complexity theories.

Water leakage through soil has been considered the most serious problem and the main cause of concrete degradation in subway facilities. Several deterioration mechanisms are derived from water intrusion, among others are concrete cracking, spalling, and water voids. These mechanisms can compromise the structural integrity and jeopardize public safety. The detection and evaluation of concrete structures are predominantly conducted on the basis of visual inspection (VI) techniques, which are known to be time-consuming, subjective, and qualitative in nature. Although, these technologies may be consistent in finding surface defects, e.g., cracks, and spalling, they fall short in detecting subsurface distresses such as air voids, and water voids. Ground penetrating radar (GPR) has been widely used for the inspection and evaluation of concrete infrastructure. Nevertheless, few research endeavors were conducted for the detection and mapping of air/water voids. This paper presents a GPR-based assessment model for subway networks. The model performs damage identification and localization of air voids and water voids in the concrete subsurface. It provides a systematic approach for the detection and mapping through the incorporation of image-based analysis (IBA) and processing techniques. First, a defect detection scheme is designed to establish a consistent inspection pattern. Second, subsurface data are collected in a subway network facility. Third, the position and dimension of the detected distresses are mapped to estimate the severity of deterioration. The proposed method was implemented on assessing a segment in Montréal subway network. Validation of the results was conducted through visual inspection, digital images, thermal images and concrete coring samples which demonstrated high correlation and compatibility with the constructed GPR-based maps. The proposed system is expected to improve the quality of decision making as it can assist transportation agencies in identifying critical deficiencies and by focusing constrained funding on most deserving assets.

Nearly 23.5 million people across the U.S. live in food deserts (FDs), or regions in which residents lack access to healthy, affordable food. Food access depends in part on individual and aggregate mobility within the FD. Therefore, the amount of people with access to healthy foods depends on the number of private vehicles per household, the walk ability of the region, and available public transit options. This study aims to assess how expanding public transit options affects food access, measured by the percentage of people lacking access to food. Object-oriented programming combining agent based modeling, discrete event simulation, and GIS is used to model and simulate FDs. A FD in Austin, Texas, with approximately 6,500 residents and a median annual income of ~$32,000 is used as a case study to demonstrate this methodology. Previous research that validated the modeling framework in this case study region justifiably treated public transit as extensive to the system. However, expanding the functionality of the model to include public transit options will allow for the impact of public transit to be evaluated in this and other FD regions. Data from publically available sources are used to establish the existing conditions within the selected FD, including resident demographics (e.g., employment rate, car ownership), resident behaviors (e.g., method of transportation for grocery trips), walking paths, spatial distribution of bus routes, and the frequency at which buses move through the system. Public transit systems were found to have significant impacts on the number of people who must walk to the store as a last resort, effectively improving food access within the case study region by up to 23%. This result demonstrates the importance of considering public transit systems in FD models, and the interconnections that exist between the built environment and food system networks.

With the current challenging state of the water infrastructure, massive amounts of investment will be needed to keep providing the same or better services to consumers. A decision will have to be made whether to maintain the status quo, which is investing in the existing infrastructure, funding investments at the parcel scale, or some mix thereof, which ultimately will affect water, wastewater, and stormwater networks regardless of the primary purpose of the intervention(s) selected. Relevant parcel-level interventions include green technologies such as green roofs and rain gardens, or rainwater harvesting systems and even greywater and wastewater treatment systems. This paper presents a theoretical analysis of the effect that interventions may have on the water, wastewater and stormwater infrastructure system overall. The results show that for a better management plan, interventions on the parcel scale have to be part of the decision making process to accurately gauge future needs.

In 2016, the European Union received 1.2 million first-time asylum seekers. Approximately 60% of these were registered in Germany. Such a sudden influx of population poses technical and managerial challenges for critical infrastructure systems due to unexpected loads on the system and a lack of front-end planning to enable the infrastructure to adapt to increased users. The potential impacts of providing water to these populations may influence how hosting communities perceive incoming displaced persons and the methods used to provide water service. This study seeks to assess these public perceptions towards various methods of providing water services to displaced persons, specifically: (1) using permanently expanded infrastructure, (2) using temporary infrastructure, or (3) making no changes to the water system and solely using preexisting infrastructure. Data for this study were collected in August 2016 via a web-based survey (n = 416) deployed to German residents to assess public views toward the provision of infrastructure service for displaced persons. Statistical modeling is used to estimate geographic locations (i.e., state of residence), socio-demographic parameters (e.g., income, educational level), and characteristics (e.g., primary news source) that influences the likelihood of the German public supporting or opposing the different methods of providing water service to displaced persons. Incorporating public perceptions into decision-making may aid decision makers in anticipating and mitigating public opposition during the provision of services, developing community-supported solutions, and assisting with the integration of displaced persons into local communities.

A Multi-purpose utility tunnel (MUT) is one of the civil infrastructures in urban areas, which accommodates several networks, such as electrical cables, gas, water, and sewer pipes, inside a tunnel. There are several benefits of MUTs compared to buried utilities. However, MUTs are not widely used at the time being due to the high initial construction cost and the need for coordination among utility owners. Building information modeling (BIM) is becoming the main coordination tool for building projects. BIM has been extended to civil infrastructures, such as bridges, roads, and sewer networks. However, BIM extension for MUT information modeling (MUTIM) is yet to be developed. This paper aims to investigate a method for extending BIM to MUT projects taking advantage of similar developments for other infrastructure systems. In addition, a systematic approach for MUTIM use cases is proposed. Five use cases of MUTIM were mentioned in this paper: (1) design review for checking compliance with standards and constructability; (2) 3D coordination for clash detection and resolution; (3) ergonomic design for human accessibility and comfort during construction, inspection and maintenance activities; (4) phase planning for construction and maintenance scheduling using 4D simulation; and (5) quantity takeoff for cost estimation. The first two MUTIM use cases are discussed in detail. A case study is developed to demonstrate the feasibility of the proposed approach. The presented MUTIM approach can improve MUT projects design and coordination efficiency, and reduce project cost, which are the main barriers for promoting MUTs.

Local governments are increasingly facing budget constraints. As a result, local government stakeholders continue to defer much needed infrastructure construction and maintenance. In an effort to expand capacity, local governments have sought partnerships with private sector and third sector partners who can offer innovative solutions to increase financial and other resources for infrastructure delivery. One innovation is crowdfunding. Crowdfunding, facilitated by online social network platforms and payment technologies, allows community members to contribute to or invest in specific projects. As such, community members can vote with their dollars to promote certain types of local infrastructure projects. In this comparative case study, the research team looks at how two different third sector partners became project sponsors by pursuing crowdfunding campaigns to pay for and deliver local infrastructure projects in their respective communities. Using a traditionally funded project within each community as a control case, preliminary findings show that crowdfunding reflects changes within local stakeholder relationships and reallocation of local government resources to projects that would otherwise not be financially feasible. The results of this research are useful for all infrastructure delivery stakeholders because innovative tools, like crowdfunding, have implications for local partnerships throughout project planning, design, construction, and operation.

Bridge maintenance decision making largely depends on the ability to predict future bridge deterioration. The increasing availability of large amounts of multi-source bridge data offers opportunities to bridge data analytics for improved bridge deterioration prediction for supporting enhanced maintenance decision making. Such data include National Bridge Inventory (NBI) and National Bridge Elements (NBE) data, bridge inspection data from bridge inspection reports, bridge health condition data from various sensors, and traffic and weather data. However, bridge data have characteristics that add to the challenges of bridge data analytics: (1) the types of data features are mixed (continuous and discrete); and (2) some of the data features are redundant and/or irrelevant. These characteristics could negatively affect the performance of bridge data analytics. Various feature discretization (FD) and feature selection (FS) methods have been proposed in the literature to deal with mixed-type and redundant/irrelevant features, respectively. However, their performance levels vary across domains and applications. There is, thus, a need to evaluate the impact of using FD and FS methods on the performance of data-driven bridge deterioration prediction. To address this need, this paper focuses on evaluating the impact of FD and FS methods on predicting deterioration using NBI data. The preliminary experimental results show that when predicting the condition ratings using NBI data, compared to the baseline: (1) the ModifiedChi2, compared to the other FD methods, achieved the highest average accuracy improvement of 37.6%; and (2) the combination of the ChiMerge FD method and the Lasso FS method, compared to the other combinations, achieved the highest average accuracy improvement of 37.7%. This shows the promise of using the ModifiedChi2 FD method alone for supporting bridge data analytics.

This paper studies the long-term performance impact of project delivery methods, specifically the effects of design-build (DB) on the ride quality of asphalt concrete pavement (ACP) highways. The international roughness index (IRI) is the prime metric used to compare long-term performance for pavement projects. The data were collected from three regions and a total of twelve projects with 227 mileposts were studied: one DB project and its comparable design-bid-build (DBB) project in each of Colorado and Virginia, and five DB projects with three comparable DBB projects in Washington. The results show that all DB projects have superior IRI performance when compared to DBB projects.

Due to heightened media attention, residential concerns regarding water quality and water infrastructure are becoming more prominent across the United States. Shrinking cities face unique water system challenges where populations are chronically declining and the financial resources available to maintain these critical infrastructure systems are also decreasing. Consequently, due to the high fixed costs associated with water infrastructure, per-capita costs increase to operate and maintain the fixed-grid system. In order to understand the public view towards water infrastructure alternatives (i.e., physical or operational alternatives) in this classification of cities, a survey was deployed to 21 U.S. shrinking cities in June 2016. Of the 85% of respondents residing in their city for more than 10 years, 39% perceived a decrease in the quality of their local water system level of service. With this in mind, respondents indicated a willingness to pay, on average, 27% higher rates for an improved level of service. Of interest to this study are questions regarding the support or opposition towards water infrastructure investments that would (1) increase both the level of service and cost, (2) stabilize the cost of service (no change in level of service), and (3) increase cost of service to cover additional infrastructure or replacement (no change in level of service). Results indicate that 61.4% of residents support increasing both the level of service and cost, 69.8% support stabilization of service costs and 48.3% support increasing their costs for additional infrastructure or replacement. This study seeks to understand the parameters that lead to supporting or opposing these infrastructure investments with respective consequential rate implications through statistical modeling. In cities where water infrastructure management is constrained by fiscal capacity, this information can assist in prioritizing capital project investments that incorporate public support, potentially increasing the sustainability of infrastructure investments.

With increasing urbanization, highway engineers have the arduous task of managing rapidly deteriorating highway infrastructure facilities with limited funds. For most of the budget allocation models proposed in the literature, there is the assumption of “one” central source of funding which can be used to fund all the different categories of maintenance projects. For municipal agencies, this is rare; there are usually multiple funding categories with restrictions on the eligible projects that can be funded by the respective funding sources. This paper aims at addressing this gap in problem formulation. First, a bi-objective base case model is constructed as an integer linear program. The objectives of the proposed model include the maximization of the condition ratings of the highway network and the minimization of road user costs. Secondly, an alternate model is developed to account for the multiplicity of funding sources and project eligibility constraints of the respective funding categories. To provide a pragmatic construct, the models are implemented using a numerical case study representative of a subset highway network (of 50 pavement sections) in Texas. For both models, the impact of incorporating user costs and the constraints of funding sources are discussed. The findings from this study indicate that failing to account for multiple funding sources and their respective funding constraints in models leads to an overestimation of the projected network-wide pavement performance. This can lead to an increase in reactive maintenance needs and faster depletion of contingency funds.

Nuclear power plants (NPPs) needs routine shutdowns, known as “outages,” for maintenance operations. A typical outage normally takes about 30 days and involve more than 2,000 contract personnel who might not necessarily be familiar with the working procedures and environments. During outages, omission errors (i.e., skip certain steps in a task) could be common and cause delays. Most omission errors are due to forgetting. Poor communication seriously aggravates the impacts of forgetting. While most corrective actions emphasized on conducting post-event meetings to highlight required procedures, forgetting is still unavoidable. To mitigate risks caused by forgetting, the nuclear industry needs properly designed communication protocols—rules that guide participants in distributing information to the right people with the right timings. Unfortunately, limited studies examined “good” communication protocols that could protect outage productivity from forgetting. This paper presents a simulation-based optimization method that focuses on the workflow of pump maintenance activities (visual inspection, pump maintenance, and functional surveillance testing) around cooling towers. The authors also introduce the Ebbinghaus Forgetting Curves as a reference to model the probability of forgetting in the simulation. The proposed optimization will automatically identify proper communication intervals by evaluating the impacts of communication times when forgetting events occur. This optimization aims at minimizing delays of the entire workflow when omission errors occur. Results indicate that the communication protocols identified can significantly reduce risks of delays in outages.

About 20% of treated drinking water is estimated to be lost in the U.S. through distributation pipeline leakage. Current leakage detection technologies are expensive, operator-dependent, time consuming, and they only reveal the snapshot status of the pipeline at the time of inspection. There is a growing interest in employing inexpensive wireless sensor networks (WSNs) to continuously monitor distribution pipeline networks and detect significant leakages in near real-time. The lack of a sustainable energy source in buried pipeline environment to power the monitoring WSNs remains to be a great challenge. This paper presents the results of a systematic experimental evaluation of the energy harvesting potential from the flow-induced vibrations of a two-looped, real-size pipeline test bed that comprises varying pipe sizes, multiple bends, T-joints, and valves. The primary objective of this paper is to determine how much energy can be harvested from the pipeline’s surface vibration and subsequently determine how variable this energy is across the two-looped pipeline network. Piezoelectric films are mounted on the pipeline surface at different locations to simultaneously collect vibrations-induced energy data. Various experimental configurations were used to evaluate the variation of energy harvesting potential across locations closer to the bends, T-joints and along straight sections of the pipeline. Results reveal the feasibility of harvesting some energy from pipeline vibrations and it is also observed that harvestable energy varies with harvesting location across a pipeline network as well as the pipe flow.

Nowadays, the urban pavement network of the city of Valencia, Spain, is based on a “worst first” approach. Under this approach, pavements showing bad condition are given higher priority to receive maintenance. In the pavement management field, this approach has been widely recognized as the least effective maintenance strategy. Given this situation, the main purpose of this study is to design and determine the general convenience of the implementation of a urban pavement management system (UPMS) in the city of Valencia. In order to do so, a basic framework of this system is proposed. This framework is aimed to be adaptable to the requirements and characteristics of the city. In order to show the potential benefits of the development and implementation of the proposed system, a feasibility analysis is also undertaken. This feasibility analysis takes into account the existing maintenance backlog derived from the current reactive policy and a life-cycle cost analysis. Results highlight the benefits derived from the implementation of this kind of systems, enabling a better definition of maintenance plans and the optimization of available funds.

Capital investment in highway infrastructure is critical to economic growth and prosperity. The inspection and timely maintenance of such assets are crucial preventative measures against their failure. However, the need to sustain such infrastructure in acceptable working conditions is continuously challenged by the rise of road repair costs, political pressures to reduce public spending, and budget deficits. This research investigates the utilization of unmanned aerial vehicles (UAVs) in assessing highway maintenance needs while reducing labor-intensive inspection. Specifically, the main objectives of this research are to: (1) explore the capacity of UAVs to collect data for roadway maintenance assessment; (2) investigate the reliability of automating pavement distress recognition using object recognition software; and (3) evaluate the viability of assessing highway maintenance needs using UAVs as compared to the traditional technique. Field experiments on collecting data using UAVs in the State of Kuwait are presented to illustrate the fulfillment of the above objectives. The results of this study should prove useful to infrastructure asset managers and departments of transportation, and could accelerate maintenance data collection, eliminate human error, and improve the reliability of maintenance assessment.

The water supply system is one of the critical infrastructure systems that provides lifeline services to society and to other infrastructure systems. Assessing and quantifying the resilience of water supply systems improves the understanding of the system’s behavior under stressed conditions and assists decision making in resilience enhancement efforts. Most of the current resilience quantification frameworks in the literature are either hazard-specific, system-limited, or limited to one or two resilience capacities. This study introduces a new framework for quantifying the resilience of water supply infrastructure with the consideration of its interdependencies with the electric distribution system. The proposed framework assesses three resilience capacities; absorptive, adaptive, and restorative resilience against three types of disruptive events: random failures, natural disasters, and deliberate attacks. The quantification framework is implemented in a network model that examines the water system’s network topology and hydraulic performance. A case study of a water supply system is presented to demonstrate the process.

Water distribution systems (WDS) are crucial for communities’ survival and economic prosperity around the world. The increasing scarcity of freshwater resources combined with deteriorating infrastructure distresses and growing number of main breaks is pushing water utilities to employ efficient reliability assessment approaches to monitor and control supply availability. Reliability evaluation of water distribution systems is a complex task as it requires both clear definition and careful computation of WDS performance in various failure states. This paper presents a comparison of two reliability measures, namely contingency reliability (CR) and minimum cut-set (MC) reliability, and demonstrates them on a benchmark WDS. This paper leverages a recently proposed non-iterative pressure driven demand (PDD) simulation approach in conjunction with EPANET hydraulic solver for the assessment of WDS performance in failure states. Both the reliability measures are separately used as objectives along with cost to design the benchmark WDS using a multi-objective evolutionary optimization algorithm. The resulting solutions from each reliability measure are comparatively assessed. Minimum cut-set was found to have performed better than CR in the comparative assessment. Both approaches were found to have certain limitations. A hybrid minimum cut-set approach in which a threshold demand-dissatisfaction that would distinguish concerning system failures from others may be more useful. Similarly, a modified contingency reliability approach that is suitable for all types of water distribution system configurations and sizes may be more useful. The identification of most competent reliability method will support optimal design and rehabilitation decision making for water distribution systems in a computationally efficient manner.

One inevitable consequence of climate change is the rising sea level, which could adversely affect critical infrastructures in the coastal regions. Thirteen percent of the world population and 39% of the U.S. population resides in such coastal regions. Specifically, water resources and supporting water infrastructure in many coastal regions have become increasingly vulnerable to both quality and capacity issues. For example, nuisance-flooding events in low-lying coastal cities and salt-water intrusion into drinking water aquifers are becoming more frequent occurrences with rising sea levels. Several coastal states have already devised and implemented water infrastructure adaptation measures to effectively address the current and anticipated challenges of sea level rise. This paper presents the preliminary results of a comprehensive synthesis of water infrastructure adaptation practices in several coastal communities. A detailed review of policy documents published by various local, state and federal water infrastructure related agencies in the U.S. are reviewed to develop the database of water infrastructure adaptation strategies described in this paper.

The goal of this research is to identify generally accepted engineering practices that can be used to minimize negative impacts of infiltration on building drainage and, ultimately, reduce litigation surrounding subsurface drainage. This research develops a process to estimate anticipated flows at the underground piping due to surface rainfall events as well as anticipated flows due to snow runoff; it represents the first step in attaining estimated flows in the subsurface pipes based on development density and soil type. Researchers use the model to generate relationships between density of development, varying soil conditions and expected subsurface flows. One specific issue that is frequently litigated is the area of onsite drainage as related to underground piping (foundation drains and underdrains) requirements. Future research will complete the model for estimating the flows from the surface to the subsurface drains.

Constructing embankments over soft soils can be problematic due to the magnitude and time associated with subsurface compression. Determining the end of primary consolidation is greatly exacerbated for layered soils that compress at varying rates. This paper discusses the use of magnet extensometer instrumentation to isolate compression within specific subsurface layers and associated techniques for estimating the time of construction induced settlement. Field data is used during construction to estimate the end of construction induced subsurface compression, which greatly affects the project schedule. This case study briefly summarizes instrumentation installation, data gathering, and the challenges associated with projecting the time of construction settlement. Two different curve fitting techniques were evaluated in this research: using standard primary consolidation equations and finite difference equations for estimating the end of primary consolidation settlement. For the site investigated, the curve fitting techniques proved to be somewhat problematic because the soil layers had small magnitudes of settlement and the transition between primary and secondary settlement was not readily apparent during the evaluation of real time field data. Using the finite difference equations also proved somewhat problematic trying to fit the full record of field data based on all of the different stages of loading. Additional lessons learned include the need for effective project communication between contractors, designers, and owners and a corresponding open discussion regarding practical settlement risk.

Ice and snow accumulation on airport paved surfaces has the potential to cause fatal accidents and monetary loss due to flight delays and cancellations. Traditional de-icing methods involving the application of chemicals or salt and employing large machines can create negative environmental and structural impact on airport infrastructure systems. These methods are also considered to be labor intensive and a safety hazard, especially in congested areas such as aprons. Heated pavement systems using electrically conductive concrete (ECON) have been proposed as a promising alternative technology for preventing ice accumulation and mitigating the adverse effects of using traditional snow removal methods. The objective of this study is to present information and experience about the design, construction procedures, and performance of heated pavement systems using jointed plain concrete pavements for the construction of large-scale heated airport pavements. It is based on detailed field demonstration of the electrically conductive concrete (ECON) heated pavement system (HPS) at the north general aviation (GA) apron of the Des Moines International Airport (DSM) in Iowa, in collaboration with contractors, and airport staff representatives. The expected outcome of this study will help the construction industry to better understand optimal ECON construction methods.

Preserving historical concrete structures recognizes the work and skills of past generations and allows the communities surrounding these pieces of history the opportunity to enjoy the character and purpose of their construction. Restoration of concrete picnic tables, constructed in the 1930s by the Civilian Conservation Corps, required researching materials and methods of construction during the original construction period. Changes in the manufacturing of cement products from 1933 to today added to the challenge. To design a new concrete that would maintain the performance of original picnic tables required new materials. The new concrete design had to be compatible with the original tables, and the construction methods had to work in the mountainous terrain of the site location. The results were determined through review of historic literature, investigating historic mix designs, use of modern technology, and laboratory experiments.

Across America and specifically in hotbed development areas like Texas, California, Florida, Nevada, and Colorado, increased development has led to an increase in construction defect litigation. One commonly cited issue, slope within 5 ft of the building foundation, often results in large litigation claims because the cost to mitigate after construction may be significant. Specifically, areas in close proximity to the foundation are alleged to improperly convey water away from the foundation and with the potential for infiltration too close to the building foundation. This research surveys existing literature on the topic of surface-water and ground-water flow from building foundations, as well as investigates existing International Building Code requirements. The research identifies a range of scenarios including soil pore space, soil water capacity, soil water movement, infiltration rates, and other code or geotechnical recommendations that illustrate the challenges associated with surface runoff within ten feet of a building foundation. This research is critical because inadequate grade adjacent to foundation is cited in a large majority of construction defect litigation cases. Initial findings suggest that a building code required minimum five percent slope for the first 10 ft may not be sufficient to ensure proper drainage, but that a more comprehensive, multi-factored approach is necessary. Such research is critical to the construction industry, and may, eventually, lead to a reduction in litigation surrounding surface drainage.

Batching of concrete is generally the proportioning of the different constituents of concrete before mixing which could be by weight or volume. Mix-design justified by trial test is the best method to achieve a concrete of desired properties. Standardized prescribed concrete (SPC) mix-design is mostly adopted in mass concreting to high strength concreting applications in most developing nations. British standards accept volume batching for SPC only in mass concrete (<15 MPa) but batching by weight for normal and higher strength concrete. Structural concrete like in storey buildings requires at least a normal strength concrete (>20 MPa) recommended to be batched by weight. Designs batched by volume have been identified as the most commonly used method in concrete production in Nigeria and most developing nations, especially by medium to small scale construction firms due to the very high cost of employing batching plants. This research work developed a modified volumetric batch mix-design that will be equivalent to SPC design mix batched by weight in normal and higher strength concrete. The physical properties of the constituent concrete materials, fine aggregate, 12 and 19 mm sized coarse aggregates were determined. The strength of SPC mix of ST2, ST4, and ST5 to British standard were determined when batched by weight and their volume equivalents mix-design batch determined. The strengths of these SPC mixes were batched by volume and their weight equivalent batch-design determined. A relationship was determined between both batching mix-design methods for all the prescribed mixes and strengths using the binder-aggregate and coarse-fine aggregate ratios, such that the preferred weight batching design mix could be achieved by a modified mix-design batched by volume. This study concludes that concrete mix-design batched by weight is superior to when batched by volume and the desired design batching by weight could be achieved by generating a modified mix-design-batch by volume. This will improve the quality of concrete storey buildings in most developing nations.

Pavement service life (PSL) is an important input in the design of new and rehabilitated pavements. It is also used in pavement management system (PMS) decision tools, life-cycle cost analysis, and in the allocation of available funds. The objective of this study is to determine the PSL of flexible pavements in Louisiana and to compare the actual PSL to the assumed service life in the design phase. To achieve this objective, the variation of pavement condition index (PCI) with pavement age was extracted from the Louisiana PMS. The rate of deterioration of PCI for each pavement section was analyzed for over 11 years of performance from 1998 until 2009. Based on this analysis, it was determined that the average PSL was 16.1, 15.2, and 12.6 years for Family 1, 2, and 3, respectively. In general, the average PSL for all pavement families was lower than the assumed design life of 20 years. Alligator cracking was the controlling failure mechanism in 48% of the pavement sections. Simple performance models were developed to predict PSL and remaining service life (RSL) knowing the age of the pavement and the drop in PCI from the date of construction to a given year.

Concrete usually undergoes stringent quality controls during its fabrication in a batching plant or when made in situ. However, there are several conditions in the construction site that may affect concrete quality and operations. Reduction in compressive strength, increment in costs of concrete fabrication and low productivity are among the consequences of adverse jobsite conditions. In this study, construction site conditions including crew experience, compaction method, mixing time, curing humidity, and curing temperature were selected as variables to conduct a full 2⁵ factorial experimental design for quantifying their effect on concrete. Cylindrical concrete samples were fabricated and evaluated under each factor combination. Concrete compressive strength as a quality metric, costs, and production rates were measured as the experimental responses. Significant affecting factors and their effects on concrete were identified through the analysis of variance (ANOVA) and used to predict concrete compressive strength, cost, and production effects. A multi-objective optimization problem based on compromised solutions was formulated to maximize both concrete quality and production rates, and to minimize operation costs. The results show that high curing humidity and temperature have a positive effect on compressive strength while high mixing times increases concrete cost and reduces productivity. The proposed optimization model provides construction managers with a tool that allows finding in-situ construction conditions to reach desired goals. Further, understanding the possible impacts of these site conditions on concrete allows taking preventive actions.

Utility adjustments continue to be a major cause of delays to highway construction projects. To minimize utility related problems, state departments of transportation (DOTs) have implemented a number of improved strategies called “best practices.” This paper presents the findings of a recent study that analyzed the costs and benefits of 45 utility adjustment best practices. The study gathered and evaluated survey responses from State DOT officials on their experiences in implementing these best practices on utility adjustment projects. A total of 42 State DOT officials participated in the survey representing 33 different states. This study analyzed the costs and benefits associated with implementing 45 best practices including the effectiveness in expediting utility adjustment, reduction in project length experienced, problems and challenges encountered as a result of these best practices, and the cost of implementing these practices. The results of this analysis provides DOT decision makers valuable information to select the most beneficial best practices to reduce utility adjustment delays and accelerate utility adjustment projects.

The co-location of utilities within transportation right-of-ways presents challenges to state transportation agencies (STAs) in coordinating with those facilities to accommodate improvements to the highway system. These sometimes complex challenges are managed through the practice of utility coordination. There are many resources available discussing the effective practices of utility coordination but they are catered to traditional (design-bid-build) project delivery. Through a case study of the utility coordination on the Louisville Southern Indiana Ohio Rivers Bridges project, this paper shares the perspective of two states (Kentucky and Indiana) conducting utility coordination on two subprojects. The Kentucky subproject was delivered through design-build while the Indiana project was delivered as a public private partnership. While these projects were somewhat distinct they were managed within one major urban project according to federal highway administration terminology. This case study presents that utility coordination is heavily impacted by contracting method and shows that best practices are not universally applicable across varying contract delivery mechanisms. In other words, there is a difference perceived in utility coordination on a design-bid-build project versus a design-build project.

Previous studies have indicated that the combination of historical data and predictive analytics can improve cost estimation in construction projects. However, a major obstacle is being able to estimate projects at the conceptual phase. In this paper, the application of decision support systems is suggested. Decision support systems are software systems that utilize sophisticated algorithmic approaches to solve problems. Selection of a suitable predictive model is requisite to support the unique needs of university related construction. This envisioned system will provide an automatic and friendly environment to support project budgeting, and making decisions among proposed project alternatives. The system will allow the adjustment of project costs to match with available resources through what-if analysis. A case study, based on construction projects at the University of Alabama, is used in this study. As an initial step toward system development, data entry forms were created on the Qualtrics platform to collect data from roofing projects on the campus. The system analyzes data through predictive analytic models and displays results onto a graphical user interface. This paper contributes to the body of knowledge by proposing the development of a decision support system, with accompanying design details, for construction cost estimation in a public university construction environment.

Requests for information (RFIs) on construction projects facilitate communication between the contractor and the owner or designer. If responses to RFIs are not made promptly, they may cause delays. With alternative project delivery methods like construction manager/general contractor (CM/GC), the contractor participates in the design phase, which provides a much broader understanding of the design. This suggests fewer RFIs for these types of projects compared with the traditional design-bid-build (D-B-B) delivery method. Additionally, projects with alternative delivery methods are frequently on accelerated schedules, which would make them sensitive to RFI response time. Research has not addressed whether or how the CM/GC project delivery method relates to RFI response time, and by corollary, potential project delays. In this research, a simulation of the RFI process was developed using the Simphony simulation software. Probability distributions for RFI creation interval times and RFI response durations were developed from CM/GC highway project data. Preliminary results provide insights into the potential delays due to RFIs. Simulation results on a 3-year CM/GC highway construction project indicate that RFI review delays could potentially generate construction delays up to 10% of the construction duration.

Achieving exemplary quality standards on delivered projects is essential for the State DOTs as this presents a direct reflection of the agency’s performance. A study conducted by DBIA shows that transportation is the fastest-growing design-build sector in the United States, with a 600% increase in the number of projects completed since 2002. The owner and the design-builder share the liability of performance in design-build projects. As a result, owner is concerned over the loss of direct control on managing quality. Additionally, DOT staffing levels have been on the decline due to barriers in hiring. In light of these developments, new challenges have emerged when it comes to managing quality assurance on delivered projects. The main objective of this study is to provide a synthesis of quality assurance (QA) practices in different state DOTs for alternative delivery projects. Our research methodology involves a two-step process. We performed a thorough content analysis on the latest quality management guidelines suggested by the FHWA and analyzed the variations in the current state-of-practice of a spectrum of DOTs across the country. To get a deeper understanding of critical issues and answers to specific questions, we conducted structured interviews of industry experts. Results indicate that more and more responsibilities of quality assurance are being transferred to design-builder teams. While the roles concerning quality control are fairly similar across all DOTs, a wide variation is observed in the quality acceptance roles. The main contribution of this research is identification of important challenges in quality assurance along with innovative approaches to overcome them.

Construction site management has always represented a challenging environment. One of the major tasks of construction site management is collecting construction material information to understand the current state of construction resources. Traditionally, the collection of construction material information relies on extensive manual inspection, which is labor-intensive, time-consuming, and subject to human error. More recently, various technologies such as radio frequency identification (RFID) have been used to monitor a variety of construction materials. The installation and operation of these technologies, however, are costly. Advances in geospatial technologies such as multi-view stereovision (MVS) and point cloud co-registration (PCC) provide new methods for collecting accurate 3-dimensional (3D) construction material information from low-cost optical sensors and unmanned airborne systems (UAS). Through a case study, this research explored the potential of using MVS and PCC for collecting construction site material information. For this case study, a small UAS was used to collect multitemporal high-spatial resolution aerial images of a construction site, while PCC was used during image processing to ensure the collected multitemporal aerial images have replicated view geometry. Then using MVS, a 3D surface model was created from Time-1 images to serve as the baseline model. Subsequently, another 3D surface model was created from Time-2 images to serve as the progressive model. Then, the known construction material dimensions were compared to measurements generated by comparing the baseline model and progressive model. Results reveal that MVS and PCC can effectively track stockpiled construction material in terms of volumetric change and area change. Operationally, MVS and PCC could be used to autonomously track stockpiled construction material rapidly and accurately with a low cost.

Lack of competition is a major challenge for transportation agencies in construction projects. As market conditions are volatile and less predictive, public highway agencies encounter a difficulty in obtaining the certain number of bidders for their projects. It is argued in the literature that the degree of competition for highway construction projects might be influenced by several factors, such as project types, geographic locations of projects, prices of resources, and construction volume. However, there has not been a comprehensive empirical study to explore the relationship between the number of bidders on highway projects and construction and economic market conditions. The objective of this study is to analyze the effects of the construction market and economic conditions on the degree of competition for highway projects. This research uses historical bid data of highway projects let in the State of Georgia, the United States, between 2005 and 2015. To achieve this objective, this paper conducts statistical regression modeling for identifying significant factors contributing to the degree of competition/number of bidders on resurfacing and widening projects. The findings of this study indicated that total contract price, number of pay item, duration, the annual total value of projects, architecture billings index, annual total number of projects, asphalt cement price index, and number of bids are significant factors that contribute to the degree of competition/number of bidders. The results of this research help public highway agencies establish bidding strategies for letting projects with an improved understanding of factors affecting the degree of competition for highway construction projects.

Project team integration is attracting interest in public projects due to the increasing success and popularity it has in the private sector of the construction industry. Public transportation projects must follow state and federal regulations for the method of procurement and delivery of a transportation project. Many traditional methods invoke more competition rather than cooperation resulting in adversarial relationships as oppose to integrated teams. Team integration incorporates differentiable goals between the major project participants into a cohesive and cooperative team and sustains the relationship under an atmosphere built on cooperation, trust, and collaboration. This study aims to measure the level of project team integration using relational contracting norms to compare to cost and schedule performance from completed transportation projects. Relational contracting norms measure the degree of perception that transportation agencies have towards the condition of the contractual relationship. With the use of a survey questionnaire and follow-up interviews, the research team collected integration measures along with project cost and schedule data from recently completed transportation projects. The collected data was evaluated using statistical correlation and regression techniques to test the assumption that an integrated project team (project integration) can impact the cost and schedule of a project as well as predict the performance of cost and schedule. The findings illustrate that project team integration correlates and can predict the change in cost performance, but project team integration does not relate significantly to schedule performance. These preliminary results provide evidence that having a team work together, cooperate, and trust one another can impact the cost performance of a transportation construction project.

Most complex projects can expect some level of rework and minor changes that can be conceptually predicted and estimated during the bidding process. However, existing literature and practitioners’ experience indicate that the true impact of late change orders and rework on labor productivity behavior is often greater than expected, and the unintended side effects are very difficult to measure. This lack of knowledge and understanding leads to inaccurate calculations of the true impact of project changes and creates an incorrect ground for future decisions. Therefore, this research aims to develop a system dynamics model to understand and analyze the fluctuations in the field labor productivity rate and behavior in response to changes in the scope of the project. The other objective of this study is to formulate and discuss management policies that limit these undesirable side effects and their implications. Based on a large-scale design-bid-build water treatment project, this research conducts a case study to monitor the behavior of changes in productivity rate due to different scale change orders. The simulation results show that if a project falls behind schedule due to a change and the project deadline remains fixed, schedule pressure leads to an initial increase in productivity up to a certain level, but eventually may lead to major employee frustration. This frustration has the potential of increasing the project duration further and makes a bad situation even worse. Schedule pressure further exacerbates the problem by typically increasing the rework fraction or the errors on the built work packages. The outcome of this study helps practitioners to utilize the developed model to monitor and track labor productivity rate changes in each individual construction project and manage institutional overtime policies accordingly.

The role of project managers (PMs) in state highway agencies (SHAs) projects cannot be undermined. They are key employees that ensure that projects abide by state and federal regulations while staying within budget and schedule constraints. Several skills and capabilities are required for PMs to be able to excel at their job. These capabilities include “hard-skills” such as technical skills and field experience and “soft-skills” such as leadership and management skills. Therefore, the Wisconsin Department of Transportation (WisDOT) constantly works on enhancing these capabilities of its PMs. To identify training needs and growth areas for PMs, several PM competency assessments were created by entities like the Project Management Institute and the Construction Industry Institute. However, these assessments tend to primarily focus on PMs responsible for vertical construction projects and, therefore, are not directly applicable to WisDOT PMs. Therefore, a team of researchers from the University of Wisconsin-Madison (UW-Madison) worked with WisDOT professionals to identify and define 55 key competencies for WisDOT PMs supplemented by 145 questions to ensure the objectivity of the assessment. These competencies are divided into five categories: industry knowledge and experience, WisDOT operational knowledge and experience, project management knowledge and experience, leadership and cognitive and personal effectiveness. A weighting system based on a sophisticated mathematical model was created by UW-Madison researchers to assign weights to different competencies within the assessment based on their relative importance. Finally, a user-friendly, excel-based tool was created to make the assessment easy to use and to provide WisDOT with relevant outputs such as individual and organization-wide training needs. This paper highlights the framework of the assessment and the scoring system and includes all competencies identified and their definitions.

Accurate mapping of buried utilities is critical to managing massive urban underground infrastructure and preventing utility incidents. Using a single sensing system such as ground penetrating radar (GPR) is usually inadequate to achieve this goal. This paper presents an information fusion approach that integrates both sensing and non-sensing data based on Dempster-Shafer (D-S) evidence theory, leading to improved accuracy and confidence in utility mapping. The GPR, utility existing records, and utility specifications are three data sources which provide evidence for the state of underground utilities. The proposed method is implemented in two steps: utility presence confirmation and utility location estimation. The detection results are fused at the decision-making level and the trust level of the fused results is also assessed. A simulation study is conducted to validate the efficacy of the method. The results suggest that the integration of sensing and non-sensing data significantly reduces the error of estimated location and enhance the confidence of the results. It proves that non-sensing data can provide valuable information for spatial reasoning and should not be ignored.

Infrastructure systems underpin every aspect of urban life. As they become ever-increasingly interdependent, malfunction of some infrastructure facilities would lead to large scale cascading failure and might have catastrophic impact on urban life. In both academia and industry, continuous efforts have been made to develop appropriate modeling and simulation approaches, in order to better understand infrastructure interdependencies and analyze infrastructure performance after disruptions. However, unfortunately, though of great importance to urban resilience, social infrastructure (also known as soft infrastructure) systems, such as health care and emergency management systems, are still excluded from most of the models from a technical point of view. The study presented in this paper adopts the viewpoint of ‘system of systems’ and emphasizes the integration of technical and social infrastructure systems. A conceptual model is thus proposed to describe respective roles of and dependencies between the two types of infrastructure systems. Concretely, three major parts, namely technical infrastructure systems, social infrastructure systems, and non-infrastructure factors, are arranged in a hierarchy structure. Technical infrastructure systems play a fundamental role in urban function, while social infrastructure systems coordinate with each other through the service provided by technical ones. To validate this model structure, this study introduces the Bayesian network structure learning and adopts a likelihood score based structure learning method. Using open data from such as bureau of statistics and utility companies from 2447 zip code areas in California, U.S., this study selects 11 variables representing some components in the three major parts in the model. The score based structure learning method is carried out using the training set with size of 2,447 to discover the underlying dependency relationships among the 11 variables. The structure learning result shows to be consistent with the expected structure in the proposed conceptual model.

Using thermography as a nondestructive method for subsurface detection of the concrete structure has been developed for decades. However, the performance of current practice is limited due to the heavy reliance on the environmental conditions as well as complex environmental noises. A non-time-series method suffers from the issue of solar radiation reflected by the target during heating stage, and issues of potential non-uniform heat distribution. These limitations are the major constraints of the traditional single thermal image method. Time series-based methods such as Fourier transform-based pulse phase thermography, principle component thermography, and high order statistics have been reported with robust results on surface reflective property difference and non-uniform heat distribution under the experimental setting. This paper aims to compare the performance of above methods to that of the conventional static thermal imaging method. The case used for the comparison is to detect voids in a hollow concrete block during the heating phase. The result was quantitatively evaluated by using signal-to-noise ratio. Favorable performance was observed using time-series methods compared to the single image approach.

This study describes the development of two piezoelectric prototypes capable of harvesting energy from the traffic on roadways. These systems utilize piezoelectric elements that respond to traffic-induced stresses. The prototypes developed involved various configurations of cylindrical piezoelectric elements. A traffic scenarios were considered for translating this power output into energy. The evaluation of the prototypes involves laboratory testing of their power output as a function of compressive stress, finite element (FE) simulation of their mechanical behavior and economic analysis of the value of the power being generated. The results available to date suggest that this technology shows promise in powering LED and low-watt sensors independently of the power grid.

Asphalt shingles are the most commonly used material on residential roofs in the United States. Asphalt is the primary input in the production of roofing asphalt shingles. In the production process of modified asphalt membranes for shingles, asphalt is modified with thermoplastic polymers such as atactic-polypropylene (APP) and styrene-butadiene-styrene (SBS). On the other hand, the use of nanoclays or organoclays is a potential alternative of traditional polymers, which are very expensive and not abundant. Nanoclays are derived from naturally occurring clay minerals and are capable of improving the physical and mechanistic properties of polymers and rubbers. Studies have showed that nanoclays improve stiffness, aging, and fire resistance behavior of asphalt binders. The objective of this study is to find out the viability of nanoclay as a modifier for asphalt binders to be used in roofing shingles and to find out the moisture susceptibility of nanoclay-modified asphalt binders by surface free energy analysis. To this end, different percentages of natural nanoclays in the form of bag fines (PBF) obtained from a local asphalt plant were used modify a base (straight run) binder. Nanoclays have not shown any detrimental effects on the delamination resistance of the binder. Thus, nanoclays are expected to be a viable alternative of expensive polymers and have potentials to reduce material costs, produce durable shingles, and induce sustainability in asphalt roofing practices in the United States.

The location and characterization of water runoff locations in canal networks is of critical importance in order to properly forecast and manage floods. Heavy rains in upstream areas can suddenly increase the rate of discharge resulting in events such as overflow, seepage losses, erosion, or flooding. The inability to simulate floods in the actual terrain often results in the actual floods developing in unexpected patterns. Thus, actual floods have been documented to occur in the inhabited side of a canal as opposed to the uninhabited embankment where managers had planned to occur. Also, warning alarms have only triggered once the flood had occurred. Additionally, nature- and human-made activities (e.g., driving trucks or cars) result in the loss of soil, creation of uneven surfaces, and erosion of edges on the canal embankment, and, overall, change the embankment profile and can alter the water runoff outlet over time. Currently, though, the manual localization of water runoff escape points is often overseen in large infrastructure networks since it demands a time-consuming, labor intensive, and prone-to-error surveying effort. The efforts in the ongoing study presented in this paper introduce a methodology to automatically detect the lowest points along canal embankments. High-resolution raster images and 3D point cloud representation of the existing canal infrastructure and surrounding areas, produced with above-the-ground photogrammetric sensors, are collected along the canals. Then, geometric algorithm, such as random sample consensus (RANSAC) is used to analyze the sensed data. This paper presents the preliminary results of an ongoing research study, showing the elevation and coordinates for the lowest and near-lowest escape outlets. Such results promise to minimize soil erosion and improve the predictability and effectiveness of flood monitoring approaches.

The Higher Education Institutions’ (HEI) asset portfolio include a diverse range of buildings with different characteristics, economic life, rehabilitation and maintenance costs, and mission criticality. All such information is to be integrated in support of a rational and highly informed decision-making process within a resource-constrained environment in the context of facilities management (FM). This process needs to build upon accurate, reliable, and timely information about various building systems, components, and component elements of the individual buildings—which comes from a variety of sources. Delivering information in a segregated manner, traditional FM tools fall short in providing requirements effectively. Building information models (BIM), capable of capturing and integrating such large information databases, has recently been recognized as a compelling tool for project life-cycle analysis. This study is the first phase of a series of research on a BIM-intensive information management framework to support FM decision-making in HEIs. Four main aspects of building FM are investigated as inputs to the framework; institutions’ asset portfolio, FM practice, FM information requirements, and employed information technology (IT) tools. Information requirements are classified into four main categories: attributes of the physical facility, operation and maintenance (O&M) data, institutional factors, and decision alternatives. This information can be captured, stored, retrieved or exchanged in multiple software packages by integrating BIMs and building operation information exchange systems within the FM framework.