Load Combinations for the Evaluation of Redundancy in Steel Bridges

Over the past decade, there has been considerable interest in the development of quantitative analytical procedures to determine if a primary steel tension member (PSTM) is a fracture critical member (FCM). Traditionally, this designation has most often been arbitrarily determined based simply on the bridge geometry, for example, the number of girders in the cross section, rather than an evaluation of the bridge in the faulted state. Clearly, such a redundancy evaluation must address the loading scenarios concurrent with failure of the PSTM, the likelihood of the member failure, the acceptable probability of load exceeding resistance in the faulted state, and the application of vehicular live load models. This research was conducted to develop a load model and load combinations that are specific to evaluating the performance of a bridge in the event a steel member was to fracture. Specifically, two load combinations were developed to evaluate the strength of a steel bridge, one for the event in which the failure of a PSTM occurs, and another for a post-failure service period. The development adhered to the reliability-based principles and procedures applied in the calculation of load combinations currently used in bridge engineering to facilitate direct implementation and to ensure consistency with current steel bridge design and evaluation procedures contained in the AASHTO LRFD Bridge Design Specifications.

Assessment of Socioeconomic Impact Diversification from Transport Infrastructure Projects: The Case of a New Regional Airport

In most cases, the decision to invest in a new airport is not simple, mainly because of the complications in the planning process, the amount of capital that needs to be invested before the establishment of the business, and the number of stakeholders involved in the decision. The decision process is more complicated in restricted economic and financing conditions, where the performance of the business plan is strongly related to regional development prospects and future airport business outputs in the medium and long term. This paper provides an evaluation methodology approach to support decisions on airport development projects. The proposed methodology provides an evaluation framework based on a combination of an ex ante assessment analysis, considering the airport’s economic impact and its contribution to a specific regional economy. The Input–Output (IO) analysis framework is used to determine the economic footprint of the airport development. A series of key performance indicators (KPIs) are introduced to review the project performance in a given economic system. The case study is examined, focussing on a new airport at Heraklion in Crete (in the Kasteli valley), one of the most attractive tourist destinations in the southeast Mediterranean. Conventional wisdom is to present a systematic approach appropriate to relevant projects, providing essential tools that support decisions at the level of strategic planning. The approach is essential to provide key messages to national governments, decision makers, and stakeholders on the contribution of an airport investment to regional economic development and its contribution to the business ecosystem in the post-COVID-19 era.

Velocity Obstacle-Based Collision Avoidance and Motion Planning Framework for Connected and Automated Vehicles

This study proposes a novel collision avoidance and motion planning framework for connected and automated vehicles based on an improved velocity obstacle (VO) method. The controller framework consists of two parts, that is, collision avoidance method and motion planning algorithm. The VO algorithm is introduced to deduce the velocity conditions of a vehicle collision. A collision risk potential field (CRPF) is constructed to modify the collision area calculated by the VO algorithm. A vehicle dynamic model is presented to predict vehicle moving states and trajectories. A model predictive control (MPC)-based motion tracking controller is employed to plan collision-avoidance path according to the collision-free principles deduced by the modified VO method. Five simulation scenarios are designed and conducted to demonstrate the control maneuver of the proposed controller framework. The results show that the constructed CRPF can accurately represent the collision risk distribution of the vehicles with different attributes and motion states. The proposed framework can effectively handle the maneuver of obstacle avoidance, lane change, and emergency response. The controller framework also presents good performance to avoid crashes under different levels of collision risk strength.

Impact of Transit Quality on Anchor-Mediated Knowledge Economies Across Large U.S. Cities

Universities, medical centers, and headquarters are the driving forces behind cities’ innovation productivity and anchor-based urban revitalization efforts, such as innovation districts. As a result, there is increasing competition for corporate anchors, as well as emerging partnerships and conflicts. In each case, transit has a major role to play. Yet we know little about precisely how transit fits into the dynamics of anchor-based revitalization. To address this empirical gap, this study employed structural equation modeling to grasp both the direct and indirect impacts of transit on the knowledge-intensive firm location in 500 large U.S. cities. We conceptualized the indirect impact of transit as mediated by anchors with a composite value that we developed to quantitatively represent the presence and size of major innovation anchors in each city. According to our findings, the positive impact of transit on a city’s overall knowledge economy occurred through its role in supporting anchor institutions, a role that, in turn, significantly increased the likelihood of knowledge-based firms locating in the city. In short, transit quality was positively associated with larger and more established anchors, as well as the availability of more employees, which expands the city’s talent pool, a critical driver of knowledge-intensive employers’ location decisions. These findings call for greater attention to be paid to transit in cities’ anchor-based urban revitalization plans and to partnerships between cities, metropolitan organizations, and anchors in planning future transit systems.

Critical Analysis of Train Derailments in Canada through Process Safety Techniques and Insights into Enhanced Safety Management Systems

Canada’s rail transportation network is a critical part of Canada’s integrated supply chain which connects industries, consumers, and resource sectors to ports on the Atlantic and Pacific coasts. One transportation activity that is essential to most industries, especially oil and manufacturing, is the rail transport of dangerous goods (DG). Although rail transportation of DG is beneficial to Canada’s economy, not paying attention to the safe transportation of these types of goods can have irreparable effects on the economy, human lives, and the environment. Recent rail accidents, such as Lake Wabamun in 2005 and Lac-Mégantic in 2013, have shown that there is still room to increase the safety of transportation of DG by rail through improving railways’ safety management systems (SMS). As a result, investigations to increase the safety of rail transportation of DG have been started. This work is part of these initiatives focusing on enhancing railways’ SMS, particularly DG main-track train derailments. The current study applied detailed root cause analysis (RCA), the bow tie analysis (BTA), and incident databases to identify the main causes and consequences of these types of accidents (2007–2017). Then, the relationship between these factors and gaps in SMS elements were identified and the frequency of each factor was investigated. The results showed that the main gaps are related to process and equipment integrity, incident investigation, and company standards, codes, and regulations. Furthermore, some useful recommendations are presented to improve the management of each SMS element and reduce these gaps.

Relating Ndesign to Field Compaction: A Case Study in Minnesota

High field density helps in increasing the durability of asphalt pavements. In a current research effort, the University of Minnesota and the Minnesota Department of Transportation (MnDOT) have been working on designing asphalt mixtures with higher field densities. One critical issue is the determination of the Ndesign values for these mixtures. The physical meaning of Ndesign is discussed first. Instead of the traditional approach, in which Ndesign represents a measure of rutting resistance, Ndesign is interpreted as an indication of the compactability of mixtures. The field density data from some recent Minnesota pavement projects are analyzed. A clear negative correlation between Ndesign and field density level is identified, which confirms the significant effect of Ndesign on the compactability and consequently on the field density of mixtures. To achieve consistency between the laboratory and field compaction, it is proposed that Ndesign should be determined to reflect the real field compaction effort. A parameter called the equivalent number of gyrations to field compaction effort (Nequ) is proposed to quantify the field compaction effort, and the Nequ values for some recent Minnesota pavement projects are calculated. The results indicate that the field compaction effort for the current Minnesota projects evaluated corresponds to about 30 gyrations of gyratory compaction. The computed Nequ is then used as the Ndesign for a Superpave 5 mixture placed in a paving project, for which field density data and laboratory performance test results are obtained. The data analysis shows that both the field density and pavement performance of the Superpave 5 mixture are significantly improved compared with the traditional mixtures. The results indicate that Nequ provides a reasonable estimation of field compaction effort, and that Nequ can be used as the Ndesign for achieving higher field densities.

Fatigue Life Predictions for a European Pavement Test Section Subjected to Individual and Platoon Truck Configurations

Truck platooning for the transportation of loads is a strategy recently proposed by the automotive sector to cope with traffic congestion, fuel consumption, and operational costs. This new way of configuring trucks changes the typical pressures pavements structures experience. For this reason, the research efforts of the pavement sector should be aligned with the automotive sector to propose road-friendly platoon configurations. This is one of the objectives of the European project ENSEMBLE. ENSEMBLE, as indicated by its acronym, works on ENabling SafE Multi-Brand pLatooning for Europe. In this context, the present study presents a real scale test done in the Applus IDIADA facilities to evaluate the fatigue behavior of a pavement structure subjected to individual and platoon truck configurations. The effects of parameters such as traffic distribution through the year and by time of day, percentage of platoons, truck loads, number of trucks in platoon configuration, lateral wandering, and inter-truck distances were evaluated. The study’s findings revealed that the reduced rest times between trucks in the platoon configuration reduce the recovery time of the asphalt layers, increasing the fatigue damage to the pavement at high temperature conditions. This underlines the need for further research to allow the proper implementation of truck platoons. For example, research is needed to define strategies to make truck platoon configurations more pavement-friendly and analyze the costs associated with the changes in the required road maintenance/rehabilitation treatments, among others.

Recycled Polyethylene Modified Asphalt Binders and Mixtures: Performance Characteristics and Environmental Impact

This study addresses the effects of recycled polyethylene (RPE) on the performances of both asphalt binders and asphalt mixtures. Whether using RPE in an asphalt mixture might leach harmful chemicals into rainwater or melted snow was also determined. Two processes, wet and dry, were used to formulate the RPE modified asphalt binders and mixtures. In the wet process, RPE was added to asphalt binder. In the dry process, it was added to heated aggregates. RPE from two sources and PG 64-22 virgin asphalt binders from two sources were used in this study. In conclusion, RPE improved the rutting resistance of the asphalt binders and asphalt mixtures. However, it had adverse effects on their resistance to intermediate-temperature and non-load associated cracking. The dry process could produce a mixture with a higher RPE dosage compared with the wet process using one virgin asphalt binder but not the other; thus, the virgin asphalt binder source was a significant factor for the dry process. Based on an embryotoxicity test, it was found that RPE can be used by the asphalt paving industry without creating any significant environmental risks.

Effects of Flexible Notice-to-Proceed Provisions on the Performance of Transportation Infrastructure Projects

When alternative contracting techniques are considered, one innovative approach for assuring the performance of a transportation infrastructure project is offering contractors flexibility about when they start the project. Although such flexible notice-to-proceed (NTP) provisions are becoming more common, quantitative studies examining their impact on project performance are nonexistent. This study investigates the likely effects of flexible NTP provisions on competitive bidding, bid prices, and contract time. A dataset gathered from the North Carolina Department of Transportation, United States, was carefully stratified by type and size of project to allow for unbiased analysis. The results from the hypothesis testing revealed that projects with flexible NTP provisions were more competitive in relation to bidding. The results also indicated a positive correlation between the length of flexible time window and award growth. This study is the first of its kind and will help state transportation agencies make better-informed decisions by providing a point of reference when adopting NTP provisions for alternative contracting projects.

Analysis and Prediction of Human Mobility in the United States during the Early Stages of the COVID-19 Pandemic using Regularized Linear Models

Since the United States started grappling with the COVID-19 pandemic, with the highest number of confirmed cases and deaths in the world as of August 2020, most states have enforced travel restrictions resulting in drastic reductions in mobility and travel. However, the long-term implications of this crisis to mobility still remain uncertain. To this end, this study proposes an analytical framework that determines the most significant factors affecting human mobility in the United States during the early days of the pandemic. Particularly, the study uses least absolute shrinkage and selection operator (LASSO) regularization to identify the most significant variables influencing human mobility and uses linear regularization algorithms, including ridge, LASSO, and elastic net modeling techniques, to predict human mobility. State-level data were obtained from various sources from January 1, 2020 to June 13, 2020. The entire data set was divided into a training and a test data set, and the variables selected by LASSO were used to train models by the linear regularization algorithms, using the training data set. Finally, the prediction accuracy of the developed models was examined on the test data. The results indicate that several factors, including the number of new cases, social distancing, stay-at-home orders, domestic travel restrictions, mask-wearing policy, socioeconomic status, unemployment rate, transit mode share, percent of population working from home, and percent of older (60+ years) and African and Hispanic American populations, among others, significantly influence daily trips. Moreover, among all models, ridge regression provides the most superior performance with the least error, whereas both LASSO and elastic net performed better than the ordinary linear model.