Search Results (76)

With rising global temperatures and increasing sustainability demands, the need for advanced pavement solutions has never been greater. This study breaks new ground by integrating phase change materials (PCMs), including paraffin-based wax (Rubitherm RT55), hydrated salt (Climator Salt S10), and fatty acid (lauric acid), as binder modifiers within warm mix asphalt (WMA) mixtures. Moving beyond the traditional focus on binder-only modifications, this research utilizes recycled cigarette filters (CFs) as a dual-purpose fiber additive, directly reinforcing the asphalt mixture while simultaneously transforming a major urban waste stream into valuable infrastructure. The performance of the developed WMA mixture has been evaluated in terms of stiffness behavior using an Indirect Tensile Strength Modulus (ITSM) test, permanent deformation using a static creep strain test, and rutting resistance using the Hamburg wheel-track test. Laboratory tests demonstrated that the incorporation of PCMs and recycled CFs into WMA mixtures led to remarkable improvements in stiffness, deformation resistance, and rutting performance. Modified mixes consistently outperformed the control, achieving up to 15% higher stiffness after 7 days of curing, 36% lower creep strain after 4000 s, and 64% reduction in rut depth at 20,000 passes. Cost–benefit analysis and service life prediction show that, despite costing USD 0.71 more per square meter with 5 cm thickness, the modified WMA mixture delivers much greater durability and rutting resistance, extending service life to 19–29 years compared to 10–15 years for the control. This highlights the value of these modifications for durable, sustainable pavements. Full article

This work presents the experimental evaluation of a robotic walker following the full implementation of its sensor and motorization system. The aging population and increasing mobility impairments drive the need for assistive robotic technologies that enhance safe and independent movement. The main objective was to validate the device’s behavior in real-use scenarios by assessing its stability, responsiveness, and accuracy in detecting user movement. Tests were carried out in straight-line walking and on paths involving directional changes, both with and without motor assistance, using a cohort of five test users. Principal Component Analysis (PCA) and t-SNE dimensionality reduction techniques were applied to analyze the inertial (IMU) and proximity (TOF) sensor data, complemented by motor control monitoring through wheel Hall sensors, to explore gait patterns and system performance. Additionally, synchronized measurements between the user’s and walker’s inertial units and Time-of-Flight sensors allowed the evaluation of spatial alignment and motion correlation. The results provide a foundation for future system adjustment and optimization, ensuring the walker offers effective, safe, and adaptive assistance tailored to the user’s needs. Findings reveal that the walker successfully distinguishes individual gait patterns and adapts its behavior accordingly, demonstrating its potential for personalized mobility support. Full article

Autonomous vehicles are increasingly becoming a part of our daily lives, with active chassis control systems playing a pivotal role and drawing significant attention from both academia and industry. Current research on vehicle-to-vehicle overtaking behavior predominantly focuses on low-to-moderate speeds, with insufficient studies addressing high-speed lane-changing maneuvers. Under high-speed conditions, the variability and complexity of road environments significantly increase tracking errors, posing challenges for control algorithms that perform well at lower speeds but may suffer from reduced accuracy or instability at higher speeds. A hybrid control strategy based on vehicle dynamics for high-speed overtaking path tracking is developed to ensure vehicle stability and maneuverability. By integrating Model Predictive Control (MPC) with Four-Wheel Steering (4WS) controllers and employing a two-degree-of-freedom ideal model as the path-tracking response model, we have achieved effective control and path tracking for autonomous vehicles equipped with four-wheel steering. The effectiveness of the proposed control strategy was validated on the Carsim–Simulink integrated simulation platform. Experimental results demonstrate that this strategy offers higher path-tracking accuracy than single-controller approaches under high-speed conditions while also meeting vehicle stability requirements. The model provides robust support for enhancing the path-tracking performance of autonomous four-wheel steering vehicles at medium-to-high speeds, thereby advancing the reliability and safety of autonomous driving technology in practical applications. Full article

The design of passenger-dedicated lane width is essential for freeway reconstruction and expansion projects. However, the technical standard of lane width established in China is based on trucks. This study aims to propose a passenger-dedicated lane width calculation method for freeways based on overtaking behavior. Computer vision technology was used to extract vehicle trajectories and dimensions from videos captured by an unmanned aerial vehicle (UAV). Statistical methods such as cumulative frequency statistics, typical percentile statistics and regression analysis were employed to elaborate on the lateral displacement and distance of vehicles during overtaking. The results show that vehicles’ lateral displacements are mainly related to behaviors such as lane changing, lateral distance maintenance and lane keeping. The body width sum of parallel vehicles has little effect on the geometric center distance but significantly reduces the wheel distance when increasing. The general value of the passenger-dedicated lane width on freeways is recommended to be 3.5 m, and the limit value is 3.25 m. Compared with existing lane width calculation methods, this study pays more attention to the relationship between vehicle width and lateral distance, which can better cope with the challenges caused by vehicle diversity in lane width design. Full article

This paper presents datasets and analyses of 3D LiDAR scans capturing the rutting behavior of a rover wheel in a single-wheel terramechanics testbed. The data were acquired using a LiDAR sensor to record the terrain deformation caused by the wheel’s passage through a Toyoura sandbed, which mimics lunar regolith. Vertical loads of 25 N, 40 N, and 65 N were applied to study how rutting patterns change, focusing on rut amplitude, height, and inclination. This study emphasizes the extraction and processing of terrain profiles from noisy point cloud data, using methods like curve fitting and moving averages to capture the ruts’ geometric characteristics. A sine wave model, adjusted for translation, scaling, and inclination, was fitted to describe the wheel-induced wave-like patterns. It was found that the mean height of the terrain increases after the grouser wheel passes over it, forming ruts that slope downward, likely due to the transition from static to dynamic sinkage. Both the rut depth at the end of the wheel’s path and the incline increased with larger loads. These findings contribute to understanding wheel–terrain interactions and provide a reference for validating and calibrating models and simulations. The dataset from this study is made available to the scientific community. Full article

This study presents a method for determining the optimal gear ratio in electric trains by examining the effects of motor efficiency, wheel wear, and relative damage to the input and output shafts of the reduction gear. In electric trains, reduction gears and wheels are critical for converting the driving motor’s torque and determining the motor’s operational point, which in turn affects efficiency and durability. Over time, wheel wear from regular use and periodic profiling reduces the wheel radius, causing an effective increase in the gear ratio, which impacts the motor efficiency and load distribution across drivetrain components. This study models the dynamic behavior of the vehicle’s drivetrain system using MATLAB/Simulink and incorporates real-world data on wheel wear to address the problem. Through simulations with varying gear ratios, it analyzes changes in motor efficiency and uses Miner’s rule to assess the relative damage on the reduction gear’s input and output shafts. The results enable the identification of a gear ratio that balances motor efficiency and reduces cumulative fatigue damage, which is especially important for maintaining long-term drivetrain durability. This approach provides a systematic way to enhance the overall performance and lifespan of electric train systems by selecting a gear ratio that optimally aligns efficiency and durability. Full article

Over the past few decades, flexible pavements across the globe have seen a significant reduction in their service life due to climate changes. The flexible pavements with unsaturated subgrades undergo volumetric changes during the drying and wetting phases, affecting their long-term deformation behavior. These phases cause significant variations in matric suction and groundwater table depth. This study employs a coupled pore pressure-deformation analysis on flexible pavements to investigate the impact of groundwater table depth and suction variations in unsaturated subgrades. Finite-element simulations using the Abaqus and developed USDFLD code were validated against literature data. Sensitivity analysis was conducted by varying the suctions in subgrades during drying and subsequent wetting to evaluate the groundwater table depth. Furthermore, under heavy cyclic wheel loading, pavement-deformation analysis was conducted to investigate the influence of subgrade suction. The findings demonstrate that, after an initial drying phase at 5000 kPa suction, wetting over 180 days caused the groundwater level to rise from 5.45 m beneath the subgrade to the surface. This led to a 98% increase in surface-vertical deformations due to cyclic wheel loading after 180 days of wetting compared to the deformations during the drying phase at the same suction level. This assessment of groundwater-depth variations and long-term deformation behavior with the impact of suction improves the design and sustainability of flexible pavements. Full article

The accurate prediction of tire and brake thermomechanical behavior is crucial for various applications in the automotive industry, including vehicle dynamics analysis, racing performance optimization, and driver assistance system development. The temperature of the brakes plays a crucial role in determining the performance of rubber by altering its temperature. This change impacts the rim and the air within the tire, leading to variations in temperature and tire pressure, which consequently affect the vehicle’s overall performance. Traditionally, these components have been modeled separately, neglecting the crucial thermal interaction between them, thereby losing a lot of important information from the outside that influences the tire. This paper presents a novel method that overcomes this limitation by coupling the thermomechanical models of the tire and brake, enabling a more comprehensive understanding of their combined behavior. Therefore, the present work could be an interesting starting point to understand how a control system can be influenced by the thermodynamic of the wheel–brake system. Full article

As one of the advanced automotive chassis technologies, the steer-by-wire system offers a high level of precision, responsiveness, and controllability in the driving experience. It can also adjust and optimize parameters to adapt to the preferences of different drivers. However, when faced with the steer-by-wire system, both experienced drivers and novice drivers are in the novice stage, exhibiting learning or adaptation behaviors when using this steering system. In this paper, a small-scale pilot evaluation was conducted by means of a questionnaire survey and driving-simulator experiment, and the learning behavior and adaptability of four experienced and four novice drivers to the steer-by-wire system were analyzed when using the traditional steering system. The study found that experienced drivers show significant changes in their adaptation to the steering system, mainly due to their habitual driving with traditional steering systems. In contrast, novice drivers show no significant changes in their adaptation to the steering system, which is attributed to their lack of driving experience and skills, resulting in less sensitivity to changes in the steering system. Additionally, the study found that novice drivers under the steer-by-wire system grasp control over speed and steering-wheel angle more quickly. This research provides a reference for improving drivers’ learning and adaptation abilities to the steer-by-wire system and optimizing the design of the steer-by-wire system. Full article

In this study, finite element (FE) simulation by the software Abaqus was relied on to investigate the roll forming process of a wheel rim made of an innovative dual-phase steel, i.e., DP590, after flash butt welding (FBW). In the simulation, an FE model was generated, including the design of the dies for flaring, three-roll forming, and expansion, and detailed key processing parameters based on practical production of the selected DP590. Combined with the microstructures and properties of the weld zone (WZ) and heat-affected zones (HAZs) after FBW, the distribution of stress/strain and the change in thickness of the base metal (BM), WZ and HAZs were analyzed, and compared in the important stages of roll forming. Theoretically, the variation in the microstructure and the corresponding stress–strain behaviors of the BM, WZ, and HAZs after FBW have led to the thickness reduction of DP590 that originated from softening behaviors occurring at the region of subcritical HAZs (SCHAZs), and a small amount of tempered martensite has evidently reduced the hardness and strength of the SCHAZ. Meanwhile, the distribution of stress/strain has been influenced to some extent. Further, the study includes the influence of the friction coefficient on the forming quality of the wheel rim to guarantee the simulation accuracy in practical applications. In sum, the dual-phase steel has to be carefully applied to the wheel rim, which needs to experience the processes of FBW and roll forming, focusing on the performance of SCHAZs. Full article

During service, shoe-braked railway wheel steels are often subjected to a severe thermal cycle. Therefore, understanding the evolution of the microstructure and the resulting changes in mechanical properties during service is fundamental in the choice of steel. In previous research, the effects of the thermal loading on the microstructure and mechanical properties of five different steels for railway wheels (ER7, HYPERLOS^®, Class B, SANDLOS^® and Class C) were investigated by hardness, tensile and toughness tests, in the as-supplied condition and after different heat treatments designed to replicate the modification of the microstructure due to braking. In this paper, the tensile work hardening behavior was studied by interpolating the tensile flow curves with the constitutive equation related to the dislocation density proposed by Voce, which correlates the Voce equation parameters with the microstructural features of metallic materials. The work hardening analysis revealed that there is a good correlation between the Voce parameters and the microstructure of the five steels in as-supplied condition and after heat treatments. An interesting correlation was found between Voce parameters and apparent fracture toughness. After heat treatments at 700 °C and 750 °C the properties of the steels decreased, which was consistent with the evolution of the microstructure. However, after exposure at 970 °C with subsequent cooling in air, Class C steel appears to have a microstructure similar to the original microstructure, with tensile and toughness properties very similar to the as-supplied condition, demonstrating better microstructural stability compared to steels ER7, HYPERLOS^®, Class B and SANDLOS^®. Full article

Consumer interest in plant-based milk alternatives is growing, despite extra charges in coffeehouses. While much research exists on non-dairy alternatives, plant-based milks in coffee drinks remain understudied. This study examines consumer preferences and behaviors regarding milk alternatives in coffee, using the Theoretical Domains Framework (TDF) and the Behavior Change Wheel (BCW). A survey of 200 participants from 19 countries explored demographics, coffee habits, attitudes towards non-dairy milk charges, and marketing awareness. Market insights showed taste as the main reason for coffee choice, with a preference for cow’s milk and local cafes for quality. Many opposed the extra charges for non-dairy options, citing lactose intolerance or allergies, especially among Gen Z and Millennials. Regional variations included stronger opposition in the UK and Germany compared to the UAE and USA. The marketing for non-dairy milk was less memorable than general coffee advertisements. Regression analysis confirmed that viewing non-dairy milk as a dietary staple increased consumption, aligning with the TDF’s “Beliefs about Consequences” domain. Finally, within the BCW framework, the intervention strategies centered on training and coercion were discussed. Implementing these approaches could encourage the wider adoption of non-dairy milk options in coffee shops, fostering inclusivity, health awareness, and supporting environmental sustainability efforts. Full article

As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under changing wind speeds particularly intricate. Overcoming this challenge is critical as it enables bipedal robots to sustain more stable gaits during outdoor tasks, thereby increasing safety and enhancing operational efficiency in outdoor settings. To transcend the constraints of existing methodologies, this research introduces an adaptive bio-inspired exploration framework for bipedal robots facing wind disturbances, which is based on the Deep Deterministic Policy Gradient (DDPG) approach. This framework allows the robots to perceive their bodily states through wind force inputs and adaptively modify their exploration coefficients. Additionally, to address the convergence challenges posed by sparse rewards, this study incorporates Hindsight Experience Replay (HER) and a reward-reshaping strategy to provide safer and more effective training guidance for the agents. Simulation outcomes reveal that robots utilizing this advanced method can more swiftly explore behaviors that contribute to stability in complex conditions, and demonstrate improvements in training speed and walking distance over traditional DDPG algorithms. Full article

This study focuses on the tire–road friction estimation for the predictive control strategy of electronically limited slip differential (ELSD) to improve the handling and acceleration performance of front-wheel drive cars, which typically suffer from excessive understeer and inner drive wheel spin during acceleration while turning due to reduced vertical load on the wheel. To mitigate this, we propose a control logic for ELSD that enhances course followability and acceleration by pre-transferring the driving torque from the inside to the outside wheel, considering the estimated traction potential for rapid response. It is essential to improve the control accuracy of wheel spin prediction by predicting the friction coefficient of the road surface. Furthermore, this study extends to the analysis of vehicle dynamics during lane-change maneuvers on low-friction surfaces, emphasizing the role of accurate tire–road friction estimation in vehicle safety. A CarSim 2023-based simulation study was conducted to investigate the vehicle response on snowy roads with low friction coefficients (μ = 0.2) and low temperatures (−5 °C). The results demonstrated that even minimal steering input could result in significant side-slip angles, highlighting the nonlinear vehicle behavior and the critical need for robust traction estimation in such challenging conditions of general racing tracks. The proposed friction-estimation method was evaluated through vehicle testing and has been substantiated by patents for its originality in control and friction-estimation approaches. The outcomes of these combined methodologies underline the critical importance of tire–road friction coefficient estimation in both the effectiveness of the ELSD system and the broader context of active safety systems. Full article

A 28-week supported online intervention for pregnant women, informed by the Behavior Change Wheel Framework, was developed. The intervention included exercises, group sessions and a peer support platform. The aim of this study was to examine the potential effectiveness of the intervention in enhancing resilience and promoting maternal mental health. Using a quasi-experimental design, assessments were conducted at baseline, postintervention and follow-ups at six and 12 months after childbirth. Resilience, resilience attributes, and maternal mental health were measured using standardised scales. The intervention group received the intervention (N = 70), while the control group (N = 32) received care-as-usual. A repeated-measures ANOVA was used to determine within- and between-group changes. Results showed no significant differences between groups regarding resilience and maternal mental health. However, the intervention group demonstrated stable resilience (p = 0.320) compared to a significant decrease in the control group (p = 0.004). Within the intervention group, perceived social support remained stable during the intervention, but decreased significantly at the first follow-up (p = 0.012). All participants faced additional stress from the COVID-19 pandemic alongside the challenges of parenthood. This study contributes to maternal mental health literature with an innovative, supported online intervention. The intervention consists of different deployable components, designed to be offered online, and the current pilot data are promising. Further research is warranted to explore its full potential in clinical practice. Full article