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Women’s empowerment is a powerful engine for personal and societal economic development and well-being. Nevertheless, gender biases in physical infrastructure investments lead to negative consequences for women and children that reduce their empowerment and limit their economic benefits. Public fixed-route buses, such as those in Washington, DC, illustrate how physical transportation infrastructure has innate gender biases. These young residents likely depend on strollers to travel longer than a few blocks. The Washington Metropolitan Area Transit Authority (WMATA) runs the public transportation system in Washington, DC. In 2021, 7% of DC’s 720,000 residents were under five. WMATA maintains a fleet of approximately 1595 buses, 95% of which banned the onboarding of open strollers until recently. This ban directly limited the use of Metro buses for the caregivers of young children, primarily women. It also reduced the opportunities for these caregivers to participate in DC’s economic life. In neighborhoods dependent on buses for essential mobility, the stroller ban reduces employment, healthcare, social service, educational, and recreational offerings beyond walkable distances. This paper examines the publicly available discussions and actions that led to the updated stroller policy and offers opportunities for improving caregiver transit access in Washington, DC, and, by extension, other cities worldwide.

This study covers the structural optimization of vertical axis wind turbines (VAWTs) that can operate reliably for long periods of time in marine environments, as well as simulation analysis to evaluate their fatigue and strain resistance. Due to the nature of the marine environment, strong wind speeds and constant wave loads are applied, and VAWTs are likely to suffer from fatigue build-up and deformation problems in the long term. In this study, detailed numerical simulations were performed using ANSYS software (2024 R2) to analyze the effects of different airfoil shapes, material choices, tip speed ratios (TSRs), and foundation types on the turbine’s stress distribution and fatigue resistance. The results showed that NACA 0030 airfoil, composite steel, and single-pile foundation performed best under TSR 1.8 conditions, with the potential to reduce strain by approximately 30% and fatigue damage by approximately 25% compared to conventional structures. With this optimized combination, it was found that maintenance costs could be significantly reduced while maintaining structural stability at sea. These results could make an important contribution to the economical and durable design of VAWTs in the future.

With the extensive promotion of new energy vehicles, the number of electric vehicles (EVs) in China has increased rapidly. Electric vehicles are densely parked in garages, which means parking garages contain a large amount of idle energy storage resources. How to make this idle energy storage in garages participate in power system dispatch and evaluate the network loss and system carbon emissions considering electric vehicle energy storage has become an important research topic. The uncertainty around parking habits for electric vehicles causes it to be difficult to predict compared with the traditional energy storage system. Therefore, it is necessary to study its influence on the synergistic effect of loss reduction and carbon reduction as energy storage access. The benefits of new energy power generation output growth, energy waste reduction, and carbon emission reduction brought by loss reduction measures can be well reflected in the loss reduction index system of a power system in a low-carbon scenario. In this paper, a large amount of parking information in a certain area is collected, and the approximate parking habits of all vehicles in the simulated garage are obtained by the Monte Carlo method. Then, the load aggregation model is established, which is incorporated into the power system as an energy storage model. The synergy of loss reduction and carbon reduction is considered in this paper and comprehensively optimizes the strategy of integrating electric vehicles into the power system from the perspectives of electricity and carbon. In the scenarios of carbon flow calculation and network loss calculation, the YALMIP and CPLEX of MATLAB are applied, with various constraints input for simulation, so that the benefit evaluation method of carbon reduction and loss reduction under a coordinated transportation–electricity network is obtained.

The development of public charging infrastructure is crucial to support mass electric vehicle (EV) adoption. Although many cities worldwide have already installed an initial network of public chargers, it is often unclear whether the current supply of infrastructure is in line with demand and how many more charging stations are required to cope with future EV growth. In this sense, transactional charging data on the existing network can help answer these questions. We present a novel method that uses historical charging data as input to obtain answers to the following questions: (a) How many more chargers are required to meet future demand? and (b) Where should these new chargers be installed? By mining the individual charging behavior of EV drivers, we show that overflow dynamics can be found between charging stations. That is, when a preferred charging station is fully occupied, it is found that EV drivers divert to other charging stations nearby. Identifying these dynamics allows us to simulate the impact of a demand increase on the charging infrastructure network more accurately. We found the number of new chargers required to be significantly lower when considering overflow dynamics. Our simulations indicate that if demand is doubled, 30%–50% fewer charging points are needed compared with a situation in which overflow dynamics are neglected but the same failure rate is still maintained (i.e., percentage of failed charging sessions in the network). Determining the exact number of chargers will depend on the failure rate policymakers are willing to accept, reflecting the trade-off between charging convenience and utilization.

Currently, the adoption of electric vehicles (EV) draws much attention, as the environmental issue of reducing carbon emission is increasing worldwide. However, different countries face different challenges during this transition, particularly developing countries. This research aims to create a framework for the transition to EV in Indonesia through Agent-Based Modeling (ABM). The framework is used as the conceptual design for ABM to investigate the effect of agents’ decision-making processes at the microlevel into the number of adopted EV at the macrolevel. The cluster analysis is equipped to determine the agents’ characteristics based on the categories of the innovation adopters. There are 11 significant variables and four respondents’ clusters: innovators, early majority, late majority, and the uncategorized one. Moreover, Twitter data analytics are utilized to investigate the information engagement coefficient based on the agents’ location. The agents’ characteristics which emerged from this analysis framework will be used as the fundamental for investigating the effect of agents’ specific characteristics and their interaction through ABM for further research. It is expected that this framework will enable the discovery of which incentive scheme or critical technical features effectively increase the uptake of EV according to the agents’ specific characteristics.

The increasing burden on shipowners and shipping companies due to environmental regulations imposed by the International Maritime Organization (IMO) has led to the adoption of various compliance strategies, including the use of low-sulfur fuel, installation of scrubbers, and the use of liquefied natural gas (LNG) as an alternative fuel. LNG is particularly prevalent in dual-fuel propulsion ships, with the IMO Type C tank being the most commonly used storage facility. The structure of the IMO Type C tank comprises a pressure vessel and supporting saddles, which can be integrated or separate systems. Despite being manufactured within specified tolerances, welding-induced deformation of the tank and saddle is inevitable since the saddle is welded directly onto the hull. In integrated tank–saddle systems, this deformation can lead to cracks in the epoxy resin, which has lower strength and stiffness, as well as burn damage to the resin and wooden blocks from welding heat. In separate tank–saddle systems, installation difficulties can arise due to interference between the fuel tank system and adjacent structures, such as insulation or the fuel preparation room (FPR), resulting from saddle deformation caused by welding. This study analyzes the sensitivity of all weld lines involved in saddle installation using the direct inherent strain (DIS) method. Based on this analysis, the initial welding deformations are evaluated in relation to the welding direction and sequence. Finally, an optimized method for saddle installation is proposed to minimize deformation.

In Southeast Asian cities, it is common for logistic companies to operate a heterogeneous fleet of delivery vehicles with motorcycles being the preferred vehicle to handle the final phase of delivery. In such scenarios, heterogeneous fleet vehicle routing problem (HFVRP) is generally applied to plan an optimal delivery. However, in many downtown cores of large and rapidly developing Southeast Asian cities, HFVRP is neither viable nor reliable because of road usage restrictions. The purpose of this article is to develop and test a different approach that accurately takes these restrictions into account and provides viable and more sustainable results. Restrictions in this paper refer to situations of urban areas in Vietnam where (i) certain vehicle types are prohibited in specified areas or where narrow alleyways limit the utilization of vehicles that exceed the road capacity and (ii) certain roads are exclusive to certain vehicle types. In networks, limited access and exclusive lanes are represented as links, or arcs, exclusive to one or another. Taking these limitations into consideration, we have developed a unique model, which we have termed Vehicle Routing Problem with Exclusive Links (VRP-EL). The model was validated and tested for its performance on scenarios with varying ratios of exclusive links. Scenarios up to 500 customers were tested on a meta-heuristic algorithm, simulated annealing. VRP-EL produces realistic outcomes. Limiting certain links to be selected according to vehicle types increases overall travel distance. However, this increase outweighs the cost of re-planning and rerouting had they not been constrained initially. The reduction in traveling distance leads to fossil fuel reduction for the overall system. The estimation of reduced carbon emissions through applying the proposed model is presented. Considering the severe traffic congestion and carbon emissions caused by motorcycles in Vietnam, the proposed model leads to a sustainable road environment.

In this study, a mixed integer linear programming model that integrates multimodal transport—truck and rail—into the switchgrass-based bioethanol supply chain was formulated. The objective of this study was to minimize the total cost for cultivation and harvesting, infrastructure, the storage process, bioethanol production, and transportation. Strategic decisions, including the number and location of intermodal facilities and biorefineries, and tactical decisions, such as the amount of biomass shipped, processed, and converted into bioethanol, were validated by using North Dakota as a case study. It was found that the multimodal transport scenario was more cost effective than a single mode of transport (truck) and resulted in a lower cost for bioethanol. A sensitivity analysis was conducted to demonstrate the impact of key factors in the decision to use multimodal transport in a switchgrass-based bioethanol supply chain and on the cost of bioethanol.

Abstract Airports are moving toward utilizing clean energy technologies along with the implementation of practices that reduce local emissions. This includes replacing fossil fuel-based with electricity-based operations. These changes would significantly impact the energy demand profile of airports. Electrically-conductive concrete (ECON) is currently a focus of heated pavement design for replacing conventional snow removal practices. ECON heated pavement systems (HPSs) use electricity to heat the pavement surface. Since experimental studies are resource intensive and ECON HPS performance depends on weather conditions, developing a field data-validated numerical model enables its long term energy performance evaluation. In this research, a finite element (FE) model is developed and experimentally-validated using two proposed model-updating methods for full-scale ECON HPS test slabs constructed at Des Moines International Airport (DSM) in Iowa. The model predicts energy demands and average surface temperatures within 2% and 13% respectively. The estimated power demand ranges from 325 to 460 W/m2 for different weather conditions. The results of this study provide a validated tool that can be used to evaluate the energy demand of ECON HPS. Studying the energy demand of ECON HPS opens the way for developing control strategies to optimize its energy use which will contribute to developing sustainable communities.