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Environmental regulations can greatly affect the operation of new and existing infrastructure projects. In fact, the economic performance of infrastructure projects is closely related to environmental regulations whose landscape is extremely dynamic. To assist infrastructure project sectors in better coping with environmental regulatory changes, this study proposes guidelines for the robust adaptation to environmental regulations through information collected from an exploratory research process. As part of these guidelines, a process map model was developed that details the different stages in the environmental regulation development process, including prerulemaking, proposed rule development and publication, commenting period, final rule development and publication, and post-promulgation. Five adaptation subprocesses (i.e., regulatory horizon scanning, stakeholder engagement, risk and opportunity assessment, response strategy development, and compliance implementation) are examined to help regulated entities better adapt to regulatory changes across different regulatory stages. This information has the potential to provide companies with a structured stage-by-stage approach for dealing with uncertainties arising from environmental regulation changes. [ABSTRACT FROM AUTHOR]

Infrastructure projects experience different regulatory impacts during permitting, operations, and decommissioning. However, no framework is in place to provide a foundation for infrastructure operators and administrators to take advantage of the opportunities (e.g., gain competitive advantage) and cope with the risks (e.g., risk of noncompliance) related to regulatory requirements. This study aimed to identify the existing methodologies and emerging practices to proactively identify, evaluate, and respond to the impact of regulatory changes. To this end, an exploratory research approach was adopted, through which multiple field studies were conducted with interviewees from various functions and units of regulated entities as well as from regulatory agencies. Accordingly, this study established a future-proofing framework that enables companies operating in infrastructure sectors to more proactively respond to and comply with regulations during their projects. In general, the regulatory future-proofing framework encompasses two main components: (1) core subprocesses, which distinguish job sharing and specific responsibilities in dealing with regulatory changes; and (2) influencing factors, which represent overarching areas that make the subprocesses work more effectively. The framework was validated by experts and would enable companies to more effectively and proactively prepare for regulatory adaptation and response in infrastructure projects. [ABSTRACT FROM AUTHOR]

This paper proposed and tested an integrated textual–visual–geo framework to enhance social sensing techniques in smart city digital twins in the context of disasters. Effective and efficient disaster response and recovery require reliable situational awareness regarding infrastructure disruptions and their societal impacts. Due to the rapid unfolding and evolution of events in disasters and emergencies, typical data sensing techniques (such as remote sensing and satellite images) are not sufficient to gain reliable situational awareness about disruptions that affect communities at a local scale. Social sensing enables gathering and analyzing massive user-generated data from various sources (social media, in particular) to monitor unfolding of localized events such as infrastructure disruptions and community needs. To advance social sensing methods and their integration into digital twins of cities, this study proposes an integrated framework for detecting infrastructure disruptions based on three information elements embedded in social media content: images, texts, and geo-maps. The framework consists of three main methods: a graph-based approach for detecting critical tweets, an image-ranking algorithm for selecting important images, and a kernel density estimate for estimating the geographical scales of the disruptions. The application of the proposed framework was demonstrated in a case study of water release from flood control reservoirs in Houston during Hurricane Harvey in 2017. The findings illustrate the capabilities of the proposed framework for capturing the critical situational information and interpreting the results for situational awareness and disruption response. The proposed framework can enhance integration of social sensing elements into smart city digital twins in the context of disasters. Accordingly, the proposed framework can improve the ability of community members, volunteer responders, residents, and other stakeholders in coping with built environment disruptions in disasters. [ABSTRACT FROM AUTHOR]

A lack of consistent, reliable, and objective metrics and indicators for project controls poses major challenges for effectively measuring project progress and performance in the construction industry. Often, project managers are misled in their perceptions of project performance until the project nears its end. This lack of accurate project progress and performance information is a major issue that causes performance shortcomings and resource shortfalls. This study investigated critical factors for improving the reliability of project control systems throughout the construction project life cycle. Through conducting a survey and 10 in-depth case studies, this research identified 15 critical reliability improvement factors and 85 indicators with specific application timing and milestones. This robust framework for improving the reliability of project controls throughout the life cycle of a project was then validated by a panel of experts. The results of this study address an important gap related to the understanding of the key factors and indicators that contribute to the reliability of project control metrics and methods. Findings of this research may provide construction industry stakeholders with a tool to significantly improve the reliability of project progress and performance assessment practices. [ABSTRACT FROM AUTHOR]

The objective of this study is to create and test an integrated framework for assessment of vulnerability to uncertainty in complex projects. In the proposed framework, construction projects are conceptualized as metanetworks composed of different nodes (i.e., human agents, information, resources, and tasks) and links. The effects of uncertain events are translated into perturbations in the nodes and links of project metanetworks. These uncertainty-induced perturbations are reflected as transformations in a project's topological structure, and thus negatively affect the efficiency of the project's metanetwork. The extent of the variation in the efficiency of a project's metanetwork is used to determine the extent of vulnerability to uncertainty. The application of the proposed framework is shown in an illustrative case study related to a tunneling project. In the case study, various scenarios related to different uncertain events were simulated through the use of dynamic network analysis and Monte Carlo simulation. The illustrative case study demonstrated the application of the proposed framework for predictive assessment and proactive mitigation of vulnerability to uncertainty based on evaluation of dynamic interactions between various entities and networks in construction projects. The proposed framework integrates elements from complex systems, dynamic network analysis, and Monte Carlo simulation approaches, and it provides a novel computational framework for ex-ante evaluation of vulnerability to uncertainty in civil engineering projects. [ABSTRACT FROM AUTHOR]

The ASCE Body of Knowledge and the ABET Engineering Accreditation Commission have emphasized a broad set of competencies required by 21st century civil engineers. In addition to competencies that are traditionally technical, these organizations recognize that professional competencies such as leadership, the ability to design sustainable systems, effective communication, and interdisciplinary teamwork are among the many skills required by engineers of the future. To develop and enhance all of these proficiencies within the undergraduate curriculum, there is a need to take an approach that interconnects all of these outcomes throughout the curriculum, or a "networked" approach. This paper discusses service learning as a potential approach for facilitating the broad set of foundational, technical, and professional learning outcomes cited by ASCE and ABET, by investigating two case studies within the Engineering Projects in Community Service program at Purdue University. The case studies are two service-learning projects from one large, multidisciplinary, vertically integrated student design team. One project focuses on sustainable and energy efficient housing for Habitat for Humanity (HFH) in Indiana, whereas the other project focuses on affordable houses for HFH in Haiti. The current analysis of these cases suggest that service-learning projects can provide a unique learning experience for the students to develop and synthesize the broad set of foundational, technical, and professional skills by integrating learning outcomes [ABSTRACT FROM AUTHOR]

There is an urgent need for policies to close the existing financing gap for civil infrastructure. However, identification of the desired scenarios for the closure of the financing gap is complex because there are many factors that affect investment in infrastructure. Thus, comprehensive models are required to (1) simulate the impacts of policies, and (2) identify the highly likely scenarios for desired policy outcomes. The objective of this paper is to create a simulation model for ex-ante analysis of financing policies in highway transportation infrastructure in the United States. Using the agent-based technique, this model simulates the microbehaviors of state Departments of Transportation, private institutional investors, and the public. Using the output of the simulation model, financing landscapes of the U.S. transportation infrastructure are developed. The simulated landscape is shown to be helpful in identifying the highly likely scenarios leading to a high level of investment in highway transportation infrastructure under the existing infrastructure investment structures and budget constraints in the United States. The study presented in this paper is novel with respect to (1) the application of the system-of-systems modeling in the analysis of transportation infrastructure financing policies, (2) identification of the desired policy scenarios and their likelihoods for closure of the financing gap in the presence of uncertainties and adaptive behaviors, and (3) simulation and visualization of the impacts of financing policies at the state and national levels. The model promotes a data-driven policy analysis and provides policymakers with a tool to simultaneously account for the impacts of several factors and uncertainties. [ABSTRACT FROM AUTHOR]