Search Results (342)

Sports footwear is widely used across a range of physical activities. A key factor distinguishing running shoes from other types of footwear is the “drop,” the millimeter difference between the heel and the forefoot. This study aimed to analyze the influence of different drops (0, 5, and 10 mm) on ground reaction forces during walking and to examine the effects of sex and body mass index (BMI) under these conditions. An observational, descriptive, and cross-sectional study was conducted with 117 participants (56 men and 61 women). The Dinascan/IBV^® dynamometric platform (Instituto de Biomecánica de Valencia, Valencia, Spain) was used to measure ground reaction forces during walking (braking, take-off, propulsion, and swing forces), walking speed, and stance time. The descriptive analysis revealed comparable values for the left and right limbs, with slightly higher values observed in the right limb. Statistically significant differences were found in stance time, braking force, and swing force between the 0 mm and 10 mm drop conditions. Take-off force showed highly significant differences when comparing the 0–5 mm and 0–10 mm drop conditions. Sex-based differences were observed in all variables at the initial proposed drop condition of 0 mm, except for walking speed, possibly due to anatomical and physiological differences. Significant differences were found in stance time at 0 mm drop, braking force, and propulsion force. Highly significant values were obtained for take-off force and during the swing phase. A strong correlation was found between ground reaction forces and BMI with the different proposed drops in all forces studied, except for the support force, where a moderate correlation was obtained. Although shoe drop was found to influence ground reaction forces in this study, it is one of several factors that affect gait biomechanics. Other footwear characteristics, such as sole stiffness, material composition, weight, and elasticity, also play important roles in walking performance. Therefore, shoe drop should be considered an important but not exclusive parameter when selecting footwear. However, these results are limited to healthy young adults and may not be generalizable to other age groups or populations. Full article

As many countries transition to electric vehicles (EVs) to reduce tailpipe emissions from internal combustion engine vehicles (ICEVs), both vehicle types continue to generate non-exhaust particulate matter (PM), including tire wear, brake wear, road surface wear, and particularly road dust resuspension. Among these, road dust resuspension is a major contributor to non-exhaust PM. While factors such as vehicle weight and drivetrain configuration have been extensively studied in fleet-level research, direct comparisons between ICEVs and EVs of the same model have not been explored. This study investigates the effects of drivetrain, vehicle weight, and payload on road dust resuspension emissions from ICEV and EV models. Two experimental approaches were employed: (1) acceleration from 0 to 60 km/h, and (2) a simulated real-world driving cycle (RDC). Each test was conducted under both light and heavy payload conditions. The results show that the EV consistently emitted more PM than the ICEV during both acceleration and RDC tests, based on factory-standard vehicle weights. Under identical vehicle weight conditions, the EV demonstrated higher PM resuspension levels, likely due to its higher torque and more immediate power delivery, which increases friction between the tires and the road, particularly during rapid acceleration. Both vehicle types exhibited significant increases in PM emissions under heavy payload conditions. These findings underscore the importance of addressing non-exhaust emissions from EVs, particularly road dust resuspension, and highlight the need for further research into mitigation strategies, such as vehicle lightweighting. Full article

Public transport accidents pose a significant threat to public safety, so it is necessary to conduct an in-depth exploration of their risk mechanisms. In this study, risk factors were first identified through statistical analysis of the time, road section, type, and cause of accidents. Subsequently, the N-K model was applied to analyze the coupling effect among human, vehicle, road, environment, and management factors, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model was adopted to evaluate the centrality and causal relationship of these factors. The DEMATEL results were corrected using the coupling values obtained from the N-K model, through which the key factors affecting public transport accidents were identified. Finally, conclusions were drawn as follows: Human factors are the dominant inducement of public transport accidents, accounting for 70.86%, among which driver fatigue and weak safety awareness are the main sub-factors. The “human-vehicle-environment” triple coupling factor presents the highest risk, with a coupling value of 0.62, which is 1.77 times the average level of single-factor coupling. Seven key risk factors were identified, and their ranking by centrality from highest to lowest is: as follows driver fatigue, driver physical health, brake failure, unchannelized intersections, rainy weather, following too closely, and insufficient safety training. Among these factors, insufficient safety training exerts the strongest driving effect on other factors. Full article

The present contribution showcases the potential brake emission reduction with Cr₂O₃ (chromium oxide) and WC-CoCr (tungsten carbide–chromium–cobalt) rotor coatings, as realized in our joint public–private research consortium. Particulate matter (PM) emissions from automotive braking systems have been characterized using a pin-on-disc tribometer equipped with particle measurement devices: a CPC (Condensation Particle Counter), an APS (Aerodynamic Particle Sizer), an SMPS (Scanning Mobility Particle Sizer), and a PM_2.5 sampling unit. Brake pad samples made from the same low-steel friction material were tested against a grey flake cast iron disc and two types of custom coated discs: a Cr₂O₃-coated disc and a WC-CoCr-coated disc. The friction pairs were investigated at a constant contact pressure of 1.2 MPa while the sliding velocity varied during the test, starting with 25 sequences at 3.6 m/s, followed by 19 sequences at 6.1 m/s, and finishing with 6 sequences at 11.2 m/s. The test results show encouraging 64% to 84% reductions in particle number (PN) emissions between 4 nm and 3 µm and 84% to 95% reductions in mass emissions (PM_2.5) thanks to the respective coated discs. SEM-EDXS (Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy) analyses show that the hardness and roughness of the discs, the chemical reactivity (oxidation), and the abrasiveness of the three friction pairs are parameters that might explain this reduction in emission. Full article

The turning process is the main machining task in brake disc production, and the PCBN tool is the most suitable type of cutting tools in the machining of brake discs made of cast iron. The edge geometric optimization of the PCBN tool is the key factor to obtain a better tool performance. In this paper, the cutting simulation for the machining of cast iron with PCBN tool of grade HNMN120712 was established, which exhibits a simulation error lower than 10.8%. The optimal turning parameters were obtained by the equal material removal rate method. The edge geometric parameters were optimized in two stages: firstly, the optimal edge radius was obtained as 30 μm by the comprehensive normalization analysis of the cutting temperature and stress, and then, the chamfer width and angle were further optimized to 0.1 mm and 15°. At finally, the optimized PCBN tool was prepared and tested in the machining of brake discs; the results indicate that the designed tool exhibits an excellent tool performance with 3.4 times the tool life of the conventional tool. Full article

To address the growing need for field calibration of the optical properties of pedestrian targets used in autonomous emergency braking (AEB) tests, a novel three-dimensional multi-faceted standard body (TDMFSB) was developed. A camera-based analytical algorithm was proposed to evaluate the bidirectional reflectance distribution function (BRDF) characteristics of pedestrian targets. Additionally, a field calibration method applied in AEB testing scenarios (CPFAO and CPLA protocols) on one new and one aged typical pedestrian target of the same type revealed a 21% decrease in the BRDF uniformity of the aged target compared to the new one, confirming optical degradation due to repeated “crash–scatter–reassembly” cycles. The surface wear of the aged target on the side facing the vehicle produced a smoother surface, increasing its BRDF magnitude by 25% compared to the new target and making it easily detectable by the vehicle’s perception system. This led to “reverse scoring,” a safety risk in performance evaluation, necessitating timely calibration of AEB pedestrian targets to ensure reliable test results. The findings provide valuable insights into the development of regulatory techniques, evaluation standards, and technical specifications for test targets and offer a practical path toward full-life-cycle traceability and quality control. Full article

In railways, problems in braking and traction can be caused by so-called low-adhesion conditions. Adhesion is increased by sanding, where sand grains are blasted towards the wheel–rail contact. Despite the successful use of sanding in practice and extensive experimental studies, the physical mechanisms of adhesion increase are poorly understood. This study combines experimental work with a DEM model to aim at a deeper understanding of adhesion increase during sanding. The experimentally observed processes during sanding involve repeated grain breakage, varying sand fragment spread, formation of clusters of crushed sand powders, plastic deformation of the steel surfaces due to the high load applied and shearing of the compressed sand fragments. The developed DEM model includes all these processes. Two types of rail sand are analysed, which differ in adhesion increase in High-Pressure Torsion tests under wet contact conditions. This study shows that higher adhesion is achieved when a larger proportion of the normal load is transferred through sand–steel contacts. This is strongly influenced by the coefficient of friction between sand and steel. Adhesion is higher for larger sand grains, higher sand fragment spread, and higher steel hardness, resulting in less indentation, all leading to larger areas covered by sand. Full article

As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article

In this paper, we present the concept of “sequencing economics”, consisting of (A) segmentation, (B) construction sequencing, and (C) functions. An agglomeration is organized into segments, and sequencing economics examines the sequential process of efficiently building such segments. The functions (C) of the segments act as a master switch, an accelerator, a brake, etc. in the implementation of agglomeration policy. In this paper, we identify a master switch and an accelerator in scientific city agglomeration policy and draw two conclusions. First, in agglomeration policy, the construction of the master switch lowers “transport costs”, as derived from the monocentric city model of spatial economics by Fujita and Krugman. Second, the accelerator segment represents the activities of the service sector that have the highest forward-linkage effect in an input–output relationship. Regarding science city agglomeration policy, it can be concluded that the master switch is high-speed rail and the accelerator is research and education activities. In this paper, the new scientific urban agglomeration that emerges from monocentric cities is referred to as railroad-driven agglomeration (RDA), which is a type of transit-oriented development (TOD). This paper demonstrates that the Tsukuba Express, as a case study of RDA, caused the agglomeration of Tsukuba Science City. This paper establishes the concept of sequencing economics, a policy implementation rule that differs from Tinbergen’s rule. The latter is based on the concept of simultaneous equations, whereas the rule of sequencing economics is based on sequential equations. RDA enables middle-income countries to surpass their middle-income status. Full article

The presented research examined the impact of using biodiesel as a fuel for existing diesel engines during the transition to the broader adoption of electric vehicles powered by renewable energy or through integrated hybrid drive systems. The authors considered previous research on this topic, which is demonstrated by a literature review. This paper will utilize the findings to further explore the potential of optimizing existing engines by using biodiesel and thus propose their continued use in the transition period as one of the clean fuels. This paper outlines the standards that define fuel quality and presents a test bench equipped with an experimental engine and specialized equipment for laboratory examination, enabling the measurement of emissions and the determination of cylinder pressure. To ensure the repeatability of the experimental conditions and facilitate future comparison of the obtained results, the engine examination was conducted according to the standard ESC 13-mode test. The examination process confirmed a significant reduction in particulate matter emissions (on average 40%) but, simultaneously, an increase in nitrogen oxide emissions (on average 25%), whose level, according to data from the literature, depends on the type of raw materials used for biodiesel production. Brake thermal efficiency is higher when operating with biodiesel (on average 1.5%). Still, it was concluded that the use of biodiesel in existing diesel engines is feasible only if the engines are equipped with variable systems for automatically adjusting the compression ratio, fuel injection time, valve timing, and so on. The outcomes from the examination conducted can be further processed by applying statistical methods and represent an essential database for further research in this scientific area. Full article

Nowadays, there are many studies that have been conducted in order to reduce the emissions of modern reciprocating engines without, at the same time, having a negative impact on the performance characteristics. One method to accomplish that is by using ethanol-supplemented fuels instead of conventional gasoline. On the other side of the spectrum, spark timing is one of the most important parameters that affects the combustion mechanism inside a reciprocating engine and is basically controlled by the ignition advance of the engine. Therefore, the main purpose of this study is to investigate the effect of spark timing alteration on the performance characteristics and emissions of a modern reciprocating, naturally aspirated, aircraft SI engine (i.e., ROTAX 912s), operated under four different engine operating points (i.e., combination of engine speed and throttle opening), by using ethanol-supplemented fuel. The implementation of the aforementioned method is achieved through the use of an advanced simulating software (i.e., GT-POWER), which provides the user with the possibility to completely design a piston engine and parameterize it, by using a comprehensive single-zone phenomenological model, for any operating conditions in the entire range of its operating points. The predictive ability of the designed engine model is evaluated by comparing the results with the experimental values obtained from the technical manuals of the engine. For all test cases examined in the present work, the results are affiliated with important performance characteristics, i.e., brake power, brake torque, and brake-specific fuel consumption, as well as specific NO and CO concentrations. Thus, the primary objectives of this study were to examine and evaluate the results of the combination of using ethanol-supplemented fuel instead of gasoline and the alteration of the spark timing, to asses their effects on the basic performance characteristics and emissions of the aforementioned type of engine. By examining the results of this study, it is revealed that the increase in the ethanol concentration in the gasoline–ethanol fuel blend combined with the increase in the ignition advance might be an auspicious solution in order to meliorate both the performance and the environmental behavior of a naturally aspirated SI aircraft piston engine. In a nutshell, the outcoming results of this research show that the combination of the two methods examined may be a valuable solution if applied to existing reciprocating SI engines. Full article

Predictive maintenance in commercial aviation demands highly reliable and robust models, particularly for critical components like carbon brakes. This paper addresses two primary concerns in modeling carbon brake wear for distinct aircraft variants: (1) the choice between developing specialized models for individual aircraft types versus a unified, general model, and (2) the potential of transfer learning (TL) to boost model performance across diverse domains (e.g., aircraft types). We evaluate the trade-offs between predictive performance and computational efficiency by comparing specialized models tailored to specific aircraft types with a generalized model designed to predict continuous wear values across multiple aircraft types. Additionally, we explore the efficacy of TL in leveraging existing domain knowledge to enhance predictions in new, related contexts. Our findings demonstrate that a well-tuned generalized model supported by TL offers a viable approach to reducing model complexity and computational demands while maintaining robust and reliable predictive performance. The implications of this research extend beyond aviation, suggesting broader applications in component predictive maintenance where data-driven insights are crucial for operational efficiency and safety. Full article

The paper offers an overview of the motor vehicle brake pad wear process. Considering the types of wear that occur between the pads and the disc, the study begins by presenting Archard’s fundamental wear law. It explains how the hardness and roughness of materials can influence the wear rate. Furthermore, the analysis describes factors influencing the wear coefficient, including chemical affinity between materials, surface quality, thermo-elastic instability (TEI) of the materials, and environmental effects. The paper also presents detection systems for brake pad wear, such as sensors-based monitoring and artificial neural networks (ANNs). These systems monitor brake pad wear in real time, thereby improving the driving safety by alerting the driver to the condition of the brake pads. The principles and systems analyzed form the basis for predictive maintenance, minimizing the risks of brake failure due to excessive wear. Full article

The energy crisis and environmental pollution have driven the rapid development of new energy vehicles (NEVs). As a core technology for integrating electrification and intelligence in NEVs, the brake-by-wire (BBW) system has become a research hotspot due to its excellent braking energy recovery efficiency and precise active safety control performance. This paper provides a comprehensive review of the research progress in BBW technology for NEVs and provides a forward-looking perspective on its future development. First, the types and structures of the BBW system are introduced, and the development history and representative products are systematically reviewed. Next, this paper focuses on key technologies, such as the design and modeling methods of the BBW system, braking force optimization and distribution strategies, precise actuator control, multi-system coordination, driver operation perception, intelligent decision-making, personalized control, and fault diagnosis and fault-tolerant control. Finally, the main challenges faced in the research of BBW technology for NEVs are analyzed, and future development directions are proposed, providing insights for the optimization designs and industrial application of the BBW system in the future. Full article

Despite significant advancements in roll stability control for individual vehicle types, comparative research across on-road and off-road vehicles remains limited, hindering cross-disciplinary innovation. This study bridges this gap by systematically analyzing roll stability control in both vehicle categories, focusing on theoretical foundations, key technologies, and experimental validation methods. On-road vehicles rely on mature technologies like active suspension, braking, and steering, which enhance safety through sensor monitoring, rollover prediction, and integrated stability control. Validation is primarily performed through hardware-in-the-loop simulations and on-road testing. Off-road vehicles, operating in more complex environments with dynamic load changes and rugged terrain, emphasize adaptive leveling, direct torque control, and active steering. Their stability control strategies must also account for terrain irregularities, real-time load shifts, and extreme slopes, validated through scaled-model tests and field trials. Comparative analysis reveals that while both vehicle types face similar challenges, their control strategies differ significantly: on-road vehicles focus on handling and high-speed stability, while off-road vehicles require more robust, adaptive mechanisms to manage environmental uncertainties. Future research should explore multi-system collaborative control, such as integrating active suspension with intelligent terrain perception, to improve adaptability and robustness across both vehicle categories. Furthermore, the integration of machine learning and advanced predictive algorithms promises to enhance the intelligence and versatility of roll stability control systems. Full article