Vehicle Structure Research Articles

ANALYSIS OF THE POSSIBILITY OF USING AN AUTONOMOUS MEASUREMENT SYSTEM AND REGISTRATION OF THE ASSESSMENT OF THE LEVEL OF PROTECTION OF THE ARMOURED VEHICLE CREW

In the context of large-scale armed aggression by the Russian Federation and growing losses from mine injuries, there is a significant need to obtain objective information about the level of protection provided by military armoured vehicles. At the same time, Ukrainian defence enterprises are constantly working to develop the latest methods to improve the protection of vehicle crews from the threat of mines and explosives. There is an acute problem and an essential need to quickly improve the mine resistance of standard models of armoured vehicles and, as a result, the need to quickly determine the effectiveness of the measures taken and make engineering decisions. The basis for the development of modern mine protection equipment should be to identify the impact of the shock wave not only on the vehicle structure, but primarily on the crew members. It is possible to evaluate the results, conduct comprehensive research and provide reasonable recommendations for further work only on the basis of the results of tests (experimental physical modelling) during which physical factors affecting the crew are measured. It is impossible to carry out the necessary measurements without the use of modern sensors (sensors) in conjunction with an information and measurement system that will ensure the reception, processing and registration of information. The main criteria for selecting sensors are sensitivity, resolution, linearity, frequency response, temperature response, noise level and long-term stability.

Innovation in sustainable composite research: Investigating graphene-reinforced MMCs for liquid hydrogen storage tanks in aerospace and space exploration

The demand for lightweight materials in space exploration applications has seen a significant rise. This study presents a novel approach by integrating graphene with Aluminium alloy (AA) 2900 powder, synthesized through High energy ball milling technique. The resulting powder was used to reinforce Aluminium alloy 2195, creating metal matrix composites (MMCs) via squeeze casting. The findings demonstrate that incorporating 0.5 wt % 2D graphene nanoplatelets (2D-Grnp) in AA 2195 achieved density match, enabling homogeneous dispersion, addressing composite casting challenges. Consequently, the AA 2900 alloy embedded with 2D-Grnp facilitated the homogeneous dispersion of reinforcements during the squeeze casting process, yielding MMCs Ideal for potential use in lightweight liquid hydrogen fuel tank structures for launch vehicles. Following T8 heat treatment, the final casted composite plate exhibited significant enhancements in ultimate tensile strength, with a 4.5% increase over monolithic Al 2195-T8, exhibiting nominal reduction in elongation behavior and higher hardness. Additionally, scanning and transmission electron microscopy (SEM, TEM), Small Angle Neutron Scattering (SANS) and Electron Backscatter Diffraction (EBSD) revealed the squeeze casting technique's effectiveness by exhibiting enhanced bonding among homogeneously reinforced 2D-Grnp, T1/θ’ precipitates, and AA 2195.

Development of a feed-forward audio-visual notification system for reducing motion sickness in autonomous vehicles

To mitigate motion sickness occurring in seat positions where driving conditions cannot be predicted due to the changed interior structure of autonomous vehicles, a feed-forward audio-visual notification system was developed. The design, implemented in the driving environment, provides information through ambient light and notifying sound by predicting signal processing information, including steering angle and turn signals, to address the audio-visual impact of changes in the vehicle's direction, speed, and acceleration with feed-forward alerts. The correlation model between psychological and physiological responses was developed through measurements such as MSQ, MISC, EEG, fNIRS, and HRV during driving, quantifying the degree of motion sickness and improvement situations. The effect of visual variation by ambient light and the customized effect of notifying sound were combined to compare and analyze the degree of motion sickness reduction following the installation of the notification system.

DISSIMILAR HARDOX AND LOW-ALLOY STEEL IN EXCAVATOR STRUCTURES

In the structure of excavators and other transport vehicles, it is observed that there is an increasing necessity to weld elements from the Hardox steels. The paper verifies the possibility to obtain accurate DMW (dissimilar metal welds from totally different grades of Hardox 450 steel with S355J2 steel). The microstructure and mechanical tests of the obtained various welds were analysed. Argon-based shielding gases with micro nitrogen additions were used for MAG welding. Gas mixtures with micro nitrogen additions of up to even 2000 ppm and their use in welding are an absolute novelty. The purpose of the manuscript was to find the correct parameters of making dissimilar joints with such modern mixtures and to determine the most suitable mixture for welding Hardox steel and low-alloy steel for use in the automotive industry.

Transfer learning for crash design

When designing the structure of a new vehicle, car manufacturers need to ensure the compliance with strict safety requirements. Aiming to support the engineers in the early phase of this process, we propose a transfer learning framework for crashworthiness. This work explores the possibility to infer knowledge on future situations by exploiting data coming from past development processes. During the early phases of automotive development, assessing the crash safety implies dealing with the challenge of low data availability. Here, the engineers have no hardware test to rely on and can access only few finite element simulations. Under these circumstances, an attractive concept to investigate is the development of a machine learning approach able to learn from the past designs and to transfer the acquired knowledge to the new ones. Transfer learning can serve to this aim. With it, one learns the basic knowledge from a source domain A, and transfers it to a target domain B, characterized by low data availability. Here, we propose a transfer learning framework and apply it to an explicatory industrial crash example. The components produced in the past constitute the source domain; the new component design is the target domain. The proposed methodology can serve as an innovative solution to support car manufacturers in the early phase of vehicle development and thus improve the performance in crashworthiness scenarios.

Aerodynamic configuration of a wide-range reversible vehicle

The design of wide-range high-efficiency aerodynamic configurations is one of the most important key technologies in the research of near-space hypersonic vehicles. A double-sided intake configuration with different inlets on the upper and lower surfaces is proposed to adapt to wide-range flight. Firstly, the double-sided intake configuration’s design method and flight profile are delineated. Secondly, Computational Fluid Dynamics (CFD) numerical simulation based on multi-Graphics Processing Unit (GPU) parallel computing is adopted to evaluate the vehicle’s performance comprehensively, aiming to verify the feasibility of the proposed scheme. This evaluation encompasses a wide-range basic aerodynamic characteristics, inlet performance, and heat flux at critical locations. The results show that the inlets of the designed integration configuration can start up across Mach number 3.5 to 8. The vehicle possesses multi-point cruising capability by flipping the fuselage. Simultaneously, a 180°rotation of the fuselage can significantly decrease the heat accumulation on the lower surface of the vehicle, particularly at the inlet lip, further decreasing the temperature gradient across the vehicle structure. This study has some engineering value for the aerodynamic configuration design of wide-range vehicles. However, further study reveals that the flow phenomena at the intersection of two inlets are complex, posing potential adverse impacts on propulsion efficiency. Therefore, it is imperative to conduct additional research to delve into this matter comprehensively.

Thermo-mechanical coupling failure mechanisms of reusable SiCf/SiC composites with PyC interphase

The extreme and repeated aerothermal environments working on reusable launch vehicles bring challenges for the design of hot structure. Due to the outstanding high-temperature resistant, SiCf/SiC composite is an excellent candidate material for hot structures in re-entry vehicles. In this paper, the thermo-mechanical coupling failure mechanisms of SiCf/SiC composite are investigated comprehensively. Experimental results reveal different failure mechanisms of SiCf/SiC composites subjected to monotonic quasi-static tension at room temperature and high temperature, cyclic thermal fatigue and thermo-mechanical coupling fatigue. Cyclic thermal environment causing oxidation of interphase layer and embrittlement of fiber plays a significant role in decrease of load bearing capacity of SiCf/SiC composites. The long-term periodic fatigue load that is superimposed on the cyclic thermal condition would further deteriorate the performance of materials. To better understand the damage evolution process, a thermo-mechanical coupling fatigue model is proposed to describe the degradation of SiCf/SiC composites for different stress levels. The service life of SiCf/SiC composites is obtained, which could be used to evaluate the reusable performance of SiCf/SiC hot structure. The results of this study provide novel insights into the design of SiCf/SiC composites for reusable launch vehicles under prolonged and repeated service environment.

Parametric characterization of the Christopher–James–Patterson model for crack propagation in welded zone of A7N01 Aluminum alloys

AbstractAluminum alloy is a widely used material in railway vehicle structures. In order to accurately analyze the crack propagation mechanism of Aluminum alloy welding structures and predict their crack propagation life, this study focuses on the A7N01 Aluminum alloy and proposes a full‐field strain solution method based on the least‐squares method. For the first time, digital image correlation (DIC) experimental measurements are combined with the finite element analysis method to determine the shape and size of the plastic zone at the crack tip of the compact tension (CT) specimen. And it also calculates the crack propagation driving force parameters of the Christopher–James–Patterson (CJP) model using traditional crack propagation driving parameters. The research results revealed that the plastic zone at the crack tip captured by DIC experiments is in good agreement with the finite element simulation results. Additionally, the crack growth rate curve of the A7N01 Aluminum alloy, fitted based on the CJP model, is insensitive to the stress ratio. The results offer an effective approach to utilizing the da/dN‐∆KCJP curve in analyzing A7N01 Aluminum alloy and welded structural failures, broadening the scope of engineering applications for the CJP model.

Structural Design and Flight Simulation of Firefighting and Rescue UAV Based on Coaxial Dual Rotors

The technology of firefighting unmanned aerial vehicles (UAVs) used in fire scene reconnaissance, water disaster investigation, and rescue missions, has become a crucial asset in responding to fires and emergencies. The key to this technology is to swiftly and effectively improve the operational efficiency of UAVs. Based on the premise of rapid and effective rescue, the stability, tracking, and safety of hexacopter UAVs technology improved the design and optimization innovative design of the storage and transportation convenience structure of unmanned aerial vehicles were carried out. An innovative high-pressure ejection mechanism for fire bombs (delivery items) has been designed. So, a portable, efficient, and fast unmanned aerial vehicle structure was designed. The PX4 flight control system was used to conduct simulation experiments on the newly designed UAV, and it was found that the structural design was reasonable, and the UAV was operated smoothly and accurately during the simulation flight. This structural design and simulation analysis can provide new ideas for the design of new fire-fighting equipment.

A hybrid maintenance approach for key components of the train bogie to optimize fleet availability

In the context of intelligent transport systems and the rapid development of the global economy, railways face increasing demand to become safer, more efficient, and more sustainable. As a critical structure of the railway vehicle, the bogie, designed to support the vehicle body and transmit dynamic loads through the wheels, houses several components that are vital for the reliability and safety of the train. The maintenance of such a structure is complex and can greatly benefit from hybrid approaches that leverage the potential of condition-monitoring data in proactively identifying faults or irregularities whilst ensuring appropriate intervals that maximize the availability of resources. This paper proposes a hybrid maintenance approach that combines preventive maintenance, condition-based monitoring, and predictive maintenance for the key components of the bogie, aiming to optimize costs while exploiting potential economic savings of maintenance decisions for different grouping strategies, therefore, maximizing fleet availability. The model aims to study the feasibility and measure the expected economic returns of shifting from a complete preventive maintenance program to a hybrid program incorporating predictive maintenance tasks in selected components of the bogie. A deterioration model, along with failure rate estimation, is proposed and integrated into the optimization formulation. A case study of a railway company operating in Catalonia, Spain, is presented. The framework demonstrates flexibility in tackling current maintenance practices, including hierarchy and periodicity of maintenance tasks according to the intervention type and flexible hazard rates with three stages to mimic the bathtub curve behaviour. The results show that shifting to a hybrid maintenance plan has great potential to reduce costs.

Energy Absorption Behavior of Carbon-Fiber-Reinforced Plastic Honeycombs under Low-Velocity Impact Considering Their Ply Characteristics.

Honeycomb structures made of carbon-fiber-reinforced plastic (CFRP) are increasingly used in the aerospace field due to their excellent energy absorption capability. Attention has been paid to CFRP structures in order to accurately simulate their progressive failure behavior and discuss their ply designability. In this study, the preparation process of a CFRP corrugated sheet (half of the honeycomb structure) and a CFRP honeycomb structure was illustrated. The developed finite element method was verified by a quasi-static test, which was then used to predict the low-velocity impact (LVI) behavior of the CFRP honeycomb, and ultimately, the influence of the ply angle and number on energy absorption was discussed. The results show that the developed finite element method (including the user-defined material subroutine VUMAT) can reproduce the progressive failure behavior of the CFRP corrugated sheet under quasi-static compression and also estimate the LVI behavior. The angle and number of plies of the honeycomb structure have an obvious influence on their energy absorption under LVI. Among them, energy absorption increases with the ply number, but the specific energy absorption is basically constant. The velocity drop ratios for the five different ply angles are 79.12%, 68.49%, 66.88%, 66.86%, and 60.02%, respectively. Therefore, the honeycomb structure with [0/90]s ply angle had the best energy absorption effect. The model proposed in this paper has the potential to significantly reduce experimental expenses, while the research findings can provide valuable technical support for design optimization in aerospace vehicle structures.

An evaluation of front seat distance from rear facing child restraint systems in prevention of injury in frontal crash tests

Objectives Elevated head injury incidence in infants compared to toddlers involved as occupants in motor vehicle crashes has been demonstrated in multiple population-representative crash databases. Further, experimental studies have revealed a potential injury mechanism via impact between a rear-facing, CRS-restrained child and the back of the vehicle seat or console on the row in front of the CRS. Subsequently, experimental studies have suggested that bracing the CRS against the seat immediately in front of the CRS could mitigate head injury, but also indicated that more research was necessary. Thus, we investigated the effect of bracing against the front seat, as well as distance from the front seat with rear-facing infant carriers and rear-facing convertibles, with a focus on changes to measured head, neck and chest injury metrics in rear facing CRSs. Further, we examined the effect of using the infant carrier with and without a base on these injury metrics. Methods 34 frontal sled tests at 30 or 35 mph were conducted using a simulated rear-row vehicle seat and structure representing the front seatback. A Q1.5 anthropomorphic test device (ATD) was placed in a single make/model LATCH-affixed rear-facing convertible or single make/model infant carrier; infant carrier without base was affixed with lap and shoulder belt. To evaluate the effect of bracing and distance, tests were conducted with a 300, 140, 70, or 15 mm gap between the CRS seatback and the front seatback, or a touching (0 mm) or braced (-20 mm) condition. Bayesian regression models quantified the effects of various predictors and model uncertainty. Results For tests with the convertible CRS, no head contact was observed between the head and the front vehicle seatback. For the infant carrier, head contact occurred at both 70 and 140 mm distances but not the other distances. On average, the −20, 0, or 15 mm distances yielded a 60% reduction in head injury criterion with 15 millisecond window (HIC15), and a 60% to 80% reduction in neck tension, compared to the 70 and 140 mm distances; chest acceleration also decreased for the convertible seat only. In the case of both carriers and convertibles, each mm of distance the CRS moves away from the front seatback up to 70 mm, adds 5.3 HIC15 points (95% Credible Interval (CrI):[4.6, 6.2]), and 3.5 Newtons (95% CrI: [2.2, 4.8]) of neck tension, on average. Conclusions Placing a rear facing CRS, both convertibles and infant carriers, against or close to the seatback of the seat immediately in front of the CRS reduces head and tensile neck injury criteria in ATDs. The amount of gap between the front seat and the rear facing CRS is strongly and positively correlated with HIC for both convertibles and infant carriers. RF infant carriers with and without a base yield comparable injury metrics and kinematics when touching or nearly touching the back of the front vehicle seatback.

Numerical and Experimental Research on Energy Absorption Characteristics and Damage Modes of Biomimetic Anti-collision Structures for Micro Aerial Vehicles

Numerical and Experimental Research on Energy Absorption Characteristics and Damage Modes of Biomimetic Anti-collision Structures for Micro Aerial Vehicles

Hypercongestion, Autonomous Vehicles, and Urban Spatial Structure

This paper examines the effects of hypercongestion mitigation by perimeter control and the introduction of autonomous vehicles on the spatial structures of cities. By incorporating a bathtub model, we develop a land use model where hypercongestion occurs in the downtown area and interacts with land use. We show that hypercongestion mitigation by perimeter control decreases the commuting cost in the short run and results in a less dense urban spatial structure in the long run. Furthermore, we reveal that the impact of autonomous vehicles depends on the presence of hypercongestion. The introduction of autonomous vehicles may increase the commuting cost in the presence of hypercongestion and may cause a decrease in the suburban population; however, it may make cities spatially expand outward. This result contradicts that of the standard bottleneck model. When perimeter control is implemented, the introduction of autonomous vehicles decreases the commuting cost and results in a less dense urban spatial structure. These results show that hypercongestion is a key factor that can change urban spatial structures. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT25 Conference. Funding: This work was supported by ACT-X [Grant JPMJAX21AE], Fusion Oriented REsearch for disruptive Science and Technology [Grant JPMJFR215M], the Japan Society for the Promotion of Science [Grants 23K13422 and 22H01610], and the Council for Science, Technology and Innovation [Grant JPJ012187]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2024.0519 .

Sub‐6 GHz plane wave generator design for automotive antenna over‐the‐air testing

AbstractAutomotive antennas are gaining importance due to their increasingly important role for autonomous driving with the development of the Internet of Vehicles. However, over‐the‐air testing on automotive antennas is difficult owing to its large volume and complex body structure. Plane wave generators can approximate uniform plane waves in the near field of the device under test, which can greatly reduce the measurement distance and thereby decreasing the cost compared with direct far‐field solutions. This letter designs three plane wave generators for three quiet zone sizes selected according to the vehicle structure at 5.9 GHz, achieving quiet zone sizes of 1.45 m m, 2.9m m, and 3.9 m m, respectively. Within the three quiet zones, amplitude deviations of 0.82, 0.34, and 0.34 dB and phase deviations of , and are realized, respectively, according to the numerical simulations. Uncertainty analysis is further implemented to investigate the robustness of the designed PWGs proposed in this letter.

A review on the application of the boundary element method for solving acoustic eigenvalues in infinite media

Vibration analysis is fundamental in the analysis and design of rotating machinery designs, such as turbines, pumps and bearings. It is equally important in the theory of sound and is also related to the properties of electromagnetic waveguides. Its application extends to vehicle structures, equipment and design machines, both for reference and comfort. However, a vibrational analysis also has more daring purposes, directed to the definition of seismic attributes, to the dispersion of phenomena related to acoustics in infinite media. This solution can be adapted as the frequency of vibrations and how outdoor environments are designed for self-balancing devices are designed for Helmholtz self-balancing devices, which are directly adjusted. Typical pressure media situations, Boundary Element Method (BEM) is considered as one of the technical circumstances or more considered, due to its pressure field accuracy, especially differentiated by barriers and scattering of general circumstances, whose frequencies are complex numbers. This work aims to present the various particularities of BEM in approaching these problems, which involve determining the acoustic eigenvalues in open and closed domains, highlighting its operational advantages and numerical difficulties.

A day‐ahead energy management strategy for electric vehicles in parking lots considering multi‐scenario simulations and hydrogen storage system

AbstractThis article investigated the charge and discharge management structure of electric vehicles (EVs) in intelligent parking lots (IPLs). It seems that with the expansion of renewable energy sources (RESs) as clean energy and investigation of the effects of EVs on the operation and planning of future distribution networks around the way EVs exchange energy with each other and the upstream network operator, RESs such as solar and wind sources, along with hydrogen storage are essential. Therefore, a new stochastic multi‐scenario approach for charge/discharge management of EVs parked in IPL was proposed, in which a newly developed model for the IPL with a hydrogen storage system (HSS) consisting of a fuel cell, an electrolyzer, and a hydrogen storage tank was presented. In the proposed model, the constraints of upstream network and power balance constraints, with the operating constraints related to the IPL, including EVs, renewable energy sources, and the hydrogen storage system, were formulated as the most important objectives of the optimization problem. The optimization algorithm, Competitive Swarm Optimizer (CSO), was formulated for implementation, and its results were compared with those of the PSO and GWO algorithms. The CSO must handle a variety of practical, large‐scale optimization problems. Based on the obtained results, the excess energy purchased from the upstream network or renewable sources was used as hydrogen storage for consumption during peak hours. As expected, the technical constraints and financial goals of the system were met, and the proposed system was evaluated on a 33‐bus network. As the expected benefits will be the most beneficial with the presence of renewable sources, the final profit will be reduced by taking into account uncertainty for charge/discharge management in EVs such as the uncertainty of electric load, market price, wind turbine, and photovoltaic cell sources. Nonetheless, the profit obtained from renewable resources is preferable to losses resulting from the uncertainty of the system, and according to expectation, the performance of the system for managing the optimal charging and discharging of EVs in the IPL will be acceptable with the maximum profit for the grid.

Remaining Useful Life for Heavy-Duty Railway Cast Steel Knuckles Based on Crack Growth Behavior with Hypothetical Distributions

The current research on the integrity of critical structures of rail vehicles mainly focuses on the design stage, which needs an effective method for assessing the service state. This paper proposes a framework for predicting the remaining useful life (RUL) of in-service structures with and without visible cracks. The hypothetical distribution and delay time models were used to apply the equivalent crack growth life data of heavy-duty railway cast steel knuckles, which revealed the evolution characteristics of the crack length and life scores of the knuckle under different fracture failure modes. The results indicate that the method effectively predicts the RUL of service knuckles in different failure modes based on the cumulative failure probability curves for different locations and surface crack lengths. This study proposes an RUL prediction framework that supports the dynamic overhaul and state maintenance of knuckle fatigue cracks.

An optimized deep belief network based pothole detection model for asphalt road

The poor quality of asphalt roads has a significant impact on driver safety, damages the mechanical structure of vehicles, increases fuel consumption, annoys passengers and is sometimes also responsible for accidents. Further, the poor quality of the road can be described as a rough surface and the presence of potholes. The potholes can be one of the main reasons for accident cause, increased fuel consumption and annoying passengers. Furthermore, the potholes can be of varied size, radiance effect, shadow and scales. Hence, the detection of potholes in asphalt roads can be considered a complex task and one of the serious issues regarding the maintenance of asphalt roads. This work focuses on the detection of the potholes in the asphalt roads. So in this work, a pothole detection model is proposed for accurate detection of potholes in the asphalt roads. The effectiveness of the proposed pothole detection model is tested over a set of real-world image datasets. In this study, the asphalt roads of the Delhi-NCR region are chosen and real-world images of these roads are collected through the smart camera. The final road image dataset consists of a total of 1150 images including 860 pothole images and the rest of are without pothole images. Further, the deep belief network is integrated into a proposed model for the detection of pothole images as a classification task and classified the images as pothole detected and not pothole. The experimental results of the proposed detection model are evaluated using accuracy, precision, recall, F1-Score and AUC parameters. These results are also compared with ANN, SVM, VGG16, VGG19 and InceptionV3 techniques. The simulation results showed that the proposed detection model achieves a 93.04% accuracy rate, 94.30% recall rate, 96.31% precision rate and 96.92% F1-Score rate than other techniques.

The Fabrication and Testing of Unmanned Aerial Vehicle (UAV) Wing Structure Using 3D Printing and Carbon Fibre Skinning Method

This study examines the efficacy of integrating 3D printing with carbon fibre skinning to construct wing structures for Unmanned Aerial Vehicles (UAVs). The primary objective is to enhance the structural integrity and material characteristics. The study performs static load tests, which demonstrate that wings reinforced with carbon fibre lamination can endure a substantially greater maximum stress of 29.43 N, in contrast to 14.391 N for wings produced only by 3D printing. The carbon fibre laminated wings have a greater load-bearing capability, as evidenced by the safety factor study. This analysis reveals that the permitted loads for carbon fibre laminated wings (19.61 N) are higher compared to 3D printed wings (9.594 N). The tensile testing of the specimens reveals that carbon fibre laminated wings demonstrate enhanced ductility, stiffness, and yield strength. Additionally, they withstand greater levels of maximum stress and strain, except for a slightly higher stiffness seen in 3D printed wings. This research highlights that carbon fibre laminated wings are typically more durable and versatile for many uses, although 3D printed wings may be favoured in situations when greater rigidity is necessary. In conclusion, the study effectively showcases the advantages of combining 3D printing with carbon fibre skinning in the construction of UAV wings. This research significantly contributes to the progress of UAV design and provides fresh insights in the fields of aeronautical engineering and materials science. It is particularly valuable for applications that require UAVs with exceptional performance, durability, and reliability.