Search Results (47)

This study develops a compact elasticity-based framework for assessing how autonomous truck adoption influences corridor-level performance, freight demand, modal competition, and CO₂ emissions in multimodal freight Intelligent Transportation Systems. The model specifies the constant elastic (log-linear) responses of traffic performance and generalized costs to adoption, enabling the closed-form characterization of system-level rebound and road–rail reallocation effects. The analytical results show that an internal adoption threshold $P^{*}$ emerges, defined by $d\widehat{E}/dP=0$, which separates a beneficial regime (efficiency gains dominate) from an adverse regime (rebound and modal shift dominate). Comparative statics indicate that $P^{*}$ decreases with stronger ITS capability A and increases with rebound intensity R and the road–rail carbon intensity contrast K. Numerical experiments across representative corridor contexts illustrate induced demand effects exceeding 25% under high-rebound conditions and threshold ranges around $P^{*}\approx 0.3$–0.4 for plausible parameters. The results provide interpretable guidance for coordinating autonomous truck deployment with intermodal logistics design and decarbonization strategies. Full article

Decarbonizing heavy-duty freight transport is essential for achieving climate neutrality targets. Although internal combustion engine (ICE) trucks currently dominate logistics, they contribute substantially to greenhouse gas emissions. Zero-emission alternatives, such as battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (H2), provide different decarbonization pathways; however, their relative roles remain contested, particularly in small economies. While BEVs benefit from technological maturity and declining costs, hydrogen offers advantages for high-payload, long-haul operations, especially within energy-intensive cold supply chains. The aim of this paper is to examine the gradual transition from ICE trucks to hydrogen-powered vehicles with a specific focus on cold-chain logistics, where reliability and energy intensity are critical. The hypothesis is that applying a system dynamics forecasting approach, incorporating investment costs, infrastructure coverage, government support, and technological progress, can more effectively guide transition planning than traditional linear methods. To address this, the study develops a system dynamics economic model tailored to the structural characteristics of a small economy, using a European case context. Small markets face distinct constraints: limited fleet sizes reduce economies of scale, infrastructure deployment is disproportionately costly, and fiscal capacity to support subsidies is restricted. These conditions increase the risk of technology lock-in and emphasize the need for coordinated, adaptive policy design. The model integrates acquisition and maintenance costs, fuel consumption, infrastructure rollout, subsidy schemes, industrial hydrogen demand, and technology learning rates. It incorporates subsystems for fleet renewal, hydrogen refueling network expansion, operating costs, industrial demand linkages, and attractiveness functions weighted by operator decision preferences. Reinforcing and balancing feedback loops capture the dynamic interactions between fleet adoption and infrastructure availability. Inputs combine fixed baseline parameters with variable policy levers such as subsidies, elasticity values, and hydrogen cost reduction rates. Results indicate that BEVs are structurally more favorable in small economies due to lower entry costs and simpler infrastructure requirements. Hydrogen adoption becomes viable only under scenarios with strong, sustained subsidies, accelerated station deployment, and sufficient cross-sectoral demand. Under favorable conditions, hydrogen can approach cost and attractiveness parity with BEVs. Overall, market forces alone are insufficient to ensure a balanced zero-emission transition in small markets; proactive and continuous government intervention is required for hydrogen to complement rather than remain secondary to BEV uptake. The novelty of this study lies in the development of a system dynamics model specifically designed for small-economy conditions, integrating industrial hydrogen demand, policy elasticity, and infrastructure coverage limitations, factors largely absent from the existing literature. Unlike models focused on large markets or single-sector applications, this approach captures cross-sector synergies, small-scale cost dynamics, and subsidy-driven points, offering a more realistic framework for hydrogen truck deployment in small-country environments. The model highlights key leverage points for policymakers and provides a transferable tool for guiding freight decarbonization strategies in comparable small-market contexts. Full article

Transport is among the fastest-growing contributors to carbon dioxide (CO₂) emissions in the Gulf Cooperation Council (GCC) region, where rapid urbanization, population growth, and high mobility demand continue to shape energy use. This study aims to quantify the extent to which economic growth and urbanization drive transport-related CO₂ emissions across Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates between 2012 and 2022. Using sector-specific data from the International Energy Agency and World Bank, we apply panel and country-level log–log regression models to estimate long-run and short-run elasticities of transport CO₂ emissions with respect to GDP and urban population. The analysis also includes robustness checks excluding the COVID-19 pandemic year to isolate structural effects from temporary shocks. Results show that transport emissions remain strongly correlated with GDP in most countries, indicating emissions-intensive growth, while the influence of urbanization varies: positive in Kuwait and Saudi Arabia, where expansion is car-dependent, and negative in Oman and Qatar, where compact urban forms and transit investments mitigate emissions. The findings highlight the importance of differentiated policy responses—fuel-pricing reform, vehicle efficiency standards, electrification, and transit-oriented planning—to advance low-carbon mobility. By integrating elasticity-based diagnostics with decoupling analysis, this study provides the first harmonized empirical framework for the GCC to assess progress toward transport-sector decarbonization. Full article

To address the issues of capacity resource waste and increased carbon emissions caused by the asymmetry between import and export container transportation tasks in port collection and dispatching, a green and cooperative task-and-route optimization method for container trucks with heterogeneous carriers based on task sharing is proposed from the perspective of system optimization. Based on the concept of a sharing economy, a sharing and cooperation mechanism with dual elasticity in capacity and information is designed, which integrates the container trucks’ resources and dissymmetric transportation tasks of heterogeneous carriers to expand the revenue potential for all participants. Based on task sharing and matching, a green and cooperative task-and-route optimization model for container trucks with heterogeneous carriers based on task sharing is formulated in order to optimize container trucks’ resources and transportation tasks comprehensively and reduce the system’s carbon emissions. A column generation algorithm embedded with a ring-increasing strategy is designed to solve the problem to improve computational efficiency. Through algorithm testing and a case analysis, the effectiveness of the model and algorithm is validated. The optimization results show that the overall carbon emissions are reduced by more than 28%, the number of used trucks decreases by 28%, and the profits of participants are increased by 24–65% compared with independent operations. Finally, several management insights are obtained regarding the number of shared trucks, the external market demand, task demand variability, the mixed fleet composition, subsidies, and bonus adjustments. Full article

The paper industry is always looking for possible solutions for new fiber-based products, such as protective and cushioning materials. These materials must be carefully designed to provide effective cushioning while also being lightweight to reduce transportation costs. Additionally, they need to offer protection from environmental and mechanical damage, besides having good processability to ensure proper buffering. The widely used protective and cushioning materials, such as plastic foams and expanded or extruded polystyrene, create significant disposal challenges. Therefore, there is increasing demand for biodegradable and sustainable materials for cushioning applications. The focus of our research was to develop fiber-based foams and investigate the influence of different compositions (hardwood and softwood) of cellulose fibers on the basic (mass, thickness, density) and mechanical properties (three-point bend test, tensile properties). Foams made entirely from short eucalyptus fibers (100S) exhibited the highest density (28.0 ± 0.34 kg/m³) and lowest thickness (38.82 ± 4.21 mm), resulting in superior tensile strength and elastic modulus but lower strain at break. In contrast, foams composed of long spruce fibers (100L) had the lowest density (19.0 ± 0.27 kg/m³) and highest thickness (58.52 ± 1.50 mm), with lower strength and stiffness but much higher ductility and porosity (confirmed by ~30% higher air permeability compared to 100S). Blended formulations demonstrated intermediate behavior, with the 50S50L foam showing a favorable balance of strength, stiffness, and flexibility. Visual analysis confirmed heterogeneous fiber distribution with localized agglomerates and compaction at the bottom layer due to casting. To further interpret the complex relationships within the dataset and uncover patterns, Principal Component Analysis (PCA) was applied to all experimental results. The findings of the research contribute to the broader understanding of how different fiber types and blends impact the performance of sustainable cellulose-based foams, with potential implications for the development of biodegradable packaging and lightweight construction materials. Full article

This study investigates the combined influence of superabsorbent polymers (SAPs) with distinct absorption kinetics and extended mixing sequences on the rheological, mechanical, and transport properties of high-performance concrete (HPC). Two SAPs—an ionic acrylamide-co-acrylic acid copolymer (SAP-P) and a non-ionic acrylamide polymer (SAP-B)—were incorporated at an internal curing level of 100%. The impact of extended mixing times (3, 5, and 7 min) following SAP addition was systematically evaluated. Results showed that longer mixing durations led to increased superplasticizer demand and higher plastic viscosity due to continued water absorption by SAPs. However, yield stress remained relatively stable owing to the dispersing effect of the added superplasticizer. Both SAPs significantly enhanced the static yield stress and improved fresh stability, as evidenced by reduced surface settlement. Despite the rheological changes, mechanical properties—including compressive and flexural strengths and modulus of elasticity—were consistently improved, regardless of mixing duration. SAP incorporation also led to notable reductions in autogenous and drying shrinkage, as well as enhanced electrical resistivity, indicating better durability performance. These findings suggest that a 3 min extended mixing time is sufficient for effective SAP dispersion without compromising performance. Full article

Decarbonizing the transportation sector is critical for sustainable development, particularly in rapidly urbanizing countries like Turkiye. This study analyzes fuel demand elasticities for diesel, gasoline, and LPG across 12 NUTS-1 regions of Turkiye in 2022, using a panel random effects SUR approach. The model accounts for regional variation and fuel interactions, producing robust estimates that uncover significant spatial and temporal differences in consumption patterns. Uniquely, diesel demand displays a significantly positive price elasticity, challenging the conventional assumption of inelasticity. Gasoline demand is moderately price-sensitive, while LPG appears relatively unresponsive. Strong cross-price elasticities—especially between diesel and gasoline—point to substitution effects that can inform more adaptive policy frameworks. Seasonal fluctuations and Istanbul’s outsized impact also shape national trends. These findings underscore the need for differentiated region- and fuel-specific strategies. While higher gasoline taxes may effectively reduce demand, lowering diesel and LPG use will require complementary measures such as infrastructure upgrades, behavioral incentives, and accelerated adoption of alternative fuels. The study advocates for regionally adjusted carbon pricing, removal of implicit subsidies, and targeted support for electric and hybrid vehicles. Aligning fiscal tools with actual demand behavior can enhance both the efficiency and equity of the transition to a low-carbon transportation system. Full article

This study proposes replacing traditional single-value urban development intensity control with an elastic interval-based approach to address urban development challenges under population shrinkage. It constructs a Floor Area Ratio (FAR) assignment framework guided by “ideal value determination—interval value demarcation—specific value agreement”. The northern central urban area of Shantou City serves as an empirical case. The study, focusing on the conflict between inefficient expansion and population loss, delineates elastic development intensity intervals through multi-dimensional factor analysis: a baseline FAR is determined based on master plan objectives and resource carrying capacity; upper limits are calculated considering transportation and ecological constraints; and lower limits are set according to economic feasibility and social demands, forming a gradient-based control framework. Practically, the study area is divided into differentiated density units, with optimized pathways designed for newly developed, under-construction, and existing plots across multiple scenarios. A multi-stakeholder negotiation mechanism is established to dynamically adapt elastic intervals. Results demonstrate that this method maintains the regulatory authority of master plans while significantly enhancing the adaptability of spatial governance. It provides a theoretical and practical paradigm for balancing regulatory rigidity and flexibility in shrinking cities, offering actionable solutions for vacancy risk mitigation and land-use intensification. Full article

In the transportation organization optimization of high-speed railway (HSR), optimizations such as line planning, ticket pricing, and seat allocation are generally studied separately. However, in reality, when passengers choose trains, they need to consider multiple factors such as train routes, stop plans, seat prices, seat availability, and departure times. Therefore, there is an urgent need for an integrated optimization method to simultaneously make decisions regarding these multiple factors. This study constructs a nonlinear optimization model of line planning integrating differentiated pricing and seat allocation decisions for HSR under elastic demand. To efficiently solve the model, an improved heuristic algorithm based on the simulated annealing framework combined with a linear passenger flow allocation method is proposed. Finally, case analysis proves that the improved algorithm can effectively solve the model under the input conditions of an actual Y-shaped HSR network composed of 13 stations, with a potential for a 106.54% improvement from the initial solution to the final solution. The uniqueness of our study lies in the joint optimization of three critical HSR operations, which has not been comprehensively explored in prior studies and is of great significance for improving the level of HSR train operations and passenger services. Full article

The renowned van der Waals (VDW) state equation quantifies the equilibrium relationship between the pressure P, volume V, and temperature $k_{B}T$ of a real gas. We assign new variable interpretations adapted to the economic context: $P\to Y$, representing price; $V\to X$, representing demand; and $k_{B}T\to \kappa$, representing income, to describe an economic state equilibrium. With this reinterpretation, the price elasticity of demand (PED) and the income elasticity of demand (YED) are non-constant factors and may exhibit a singularity of the cusp-catastrophe type. Within this economic framework, the counterpart of VDW liquid–gas phase transition illustrates a substitution mechanism where one product or service is replaced by an alternative substitute. The conceptual relevance of this reinterpretation is discussed qualitatively and quantitatively via several illustrations ranging from transport (carpooling), medical context (generic versus original medication), and empirical data drawn from the electricity market in Germany. Full article

The term “viscoelastic pipe” refers to high polymer pipes that exhibit both elastic and viscoelastic properties. Owing to their widespread use in water transport systems, it is important to understand the transient flow characteristics of these materials for pipeline safety. Despite extensive research, these characteristics have not been sufficiently explored. This study evaluates the impact of friction models on the transient flow of viscoelastic pipes across various Reynolds numbers by employing an energy analysis approach. Given the complexity and computational demands of two-dimensional models, this paper compares the accuracy of one-dimensional and quasi-two-dimensional models. Notably, the superiority of the quasi-two-dimensional model in simulating viscoelastic pipelines is demonstrated. Owing to the interaction between pressure waves and fluid within viscoelastic pipes, fluid–structure coupling significantly attenuates pressure waves during transmission. These findings shed light on the constitutive properties of viscoelastic pipes and the influence of pipe wall friction models on transient hydraulic characteristics, building upon prior studies focused on elastic pipes. Nevertheless, numerous factors affecting transient flow in viscoelastic pipes remain unexplored. This paper suggests further analysis of strain effects, starting with temperature and pipe dynamics, to enhance the understanding of the coupling laws and flow mechanisms in viscoelastic pipelines. Full article

To optimize the evacuation process of rail transit passenger flows, the influence of the feeder bus network on bus demand is pivotal. This study first examines the transportation mode preferences of rail transit station passengers and addresses the feeder bus network’s optimization challenge within a three-dimensional framework, incorporating an elastic mechanism. Consequently, a strategic planning model is developed. Subsequently, a multi-objective optimization model is constructed to simultaneously increase passenger numbers and decrease both travel time costs and bus operational expenses. Due to the NP-hard nature of this optimization problem, we introduce an enhanced non-dominated sorting genetic algorithm, INSGA-II. This algorithm integrates innovative encoding and decoding rules, adaptive parameter adjustment strategies, and a combination of crowding distance and distribution entropy mechanisms alongside an external elite archive strategy to enhance population convergence and local search capabilities. The efficacy of the proposed model and algorithm is corroborated through simulations employing standard test functions and instances. The results demonstrate that the INSGA-II algorithm closely approximates the true Pareto front, attaining Pareto optimal solutions that are uniformly distributed. Additionally, an increase in the fleet size correlates with greater passenger volumes and higher operational costs, yet it substantially lowers the average travel cost per customer. An optimal fleet size of 11 vehicles is identified. Moreover, expanding feeder bus routes enhances passenger counts by 18.03%, raises operational costs by 32.33%, and cuts passenger travel time expenses by 21.23%. These findings necessitate revisions to the bus timetable. Therefore, for a bus network with elastic demand, it is essential to holistically optimize the actual passenger flow demand, fleet size, bus schedules, and departure frequencies. Full article

The railway industry is seeking high-performance and sustainable solutions for sub-ballast materials, particularly in light of increasing cargo transport demands and climate events. The meticulous design and construction of track bed geomaterials play a crucial role in ensuring an extended track service life. The global push for sustainability has prompted the evaluation of recycling ballast waste within the railway sector, aiming to mitigate environmental contamination, reduce the consumption of natural resources, and lower costs. This study explores materials for application and compaction using a formation rehabilitation machine equipped with an integrated ballast recycling system designed for heavy haul railways. Two recycled ballast-stabilised soil materials underwent investigation, meeting the necessary grain size distribution for the proper compaction and structural conditions. One utilised a low-bearing-capacity silty sand soil stabilised with recycled ballast fouled waste (RFBW) with iron ore at a 3:7 weight ratio, while the second was stabilised with 3% cement. Laboratory tests were conducted to assess their physical, chemical, and mechanical properties, and a non-linear elastic finite element numerical model was developed to evaluate the potential of these alternative solutions for railway sub-ballast. The findings indicate the significant potential of using soils stabilised with recycled fouled ballast as sub-ballast for heavy haul tracks, underscoring the advantages of adopting sustainable sub-ballast solutions through the reuse of crushed deteriorated ballast material. Full article

Introducing Advanced Air Mobility (AAM) as a novel transportation mode poses unique challenges due to limited practical and empirical data. One of these challenges involves accurately estimating future passenger demand and the required number of air taxis, given uncertainties in modal shift dynamics, induced traffic patterns, and long-term price elasticity. In our study, we use mobility data obtained from a Dresden traffic survey and modal shift rates to estimate the demand for AAM air taxi operations for this regional use case. We organize these operations into an air taxi rotation schedule using a Mixed Integer Linear Programming (MILP) optimization model and set a tolerance for slight deviations from the requested arrival times for higher productivity. The resulting schedule aids in determining the AAM fleet size while accounting for flight performance, energy consumption, and battery charging requirements tailored to three distinct types of air taxi fleets. According to our case study, the methodology produces feasible and high-quality air taxi flight rotations within an efficient computational time of 1.5 h. The approach provides extensive insights into air taxi utilization, charging durations at various locations, and assists in fleet planning that adapts to varying, potentially uncertain, traffic demands. Our findings reveal an average productivity of 12 trips per day per air taxi, covering distances from 13 to 99 km. These outcomes contribute to a sustainable, business-focused implementation of AAM while highlighting the interaction between operational parameters and overall system performance and contributing to vertiport capacity considerations. Full article

Connection behavior significantly influences the design efficiency of steel–concrete composite bridges. This study investigates the impact of shear connectors, specifically headed stud connectors, on the structural response of symmetric and skewed composite steel–concrete bridges. Utilizing bilinear or trilinear slip–shear strength laws for studs, in line with the existing literature and code provisions, a finite element (FE) model is developed. This FE model is applied to a case study for composite deck analysis, incorporating variations in connection strength and ductility for nonlinear analyses. The study assesses ductility demands in connections for symmetric and skewed bridges of varying lengths and angles, considering both ductile and elastic designs. Results emphasize the importance of stud capacity, ductility, and strength on the overall bridge response, analyzing slip and shear trends at the interface. Skewed bridges, crucial for non-orthogonal crossings of roads, are integral to modern transportation infrastructure. However, skewness angles exceeding 20° can result in undesirable effects on stresses in the deck due to vertical loads. The results indicate that shear distribution in studs changes significantly as the skew angle increases, contributing valuable insights into optimizing bridge design. Thus, this research provides a comprehensive analysis of principles, design methodologies, and practical applications for both symmetric and skewed steel–concrete composite bridges, considering various parameters. Full article