The objective of this study is to mitigate the bottom-out failure and improve the energy absorption of conventional helmet liners during high-energy impacts, thereby reducing the risk of head injuries. To this end, a locally reinforced Primitive-type triply periodic minimal surface (P-TPMS) energy-absorbing liner is proposed for the helmet forehead region, which facilitates progressive energy dissipation through layer-by-layer buckling deformation. A finite element model of a helmet-head coupling was created based on a previously verified high-fidelity head model and subsequently validated against the ECE 22.06 standard drop-test methodology. Three critical design parameters-outer protective layer thickness, triply periodic minimal surface (TPMS) unit cell size, and wall thickness-were optimized employing the Box-Behnken Design (BBD) response surface methodology, resulting in quadratic regression models for the head injury criteria (HIC) and peak linear acceleration (PLA) with good fit (R2 > 0.97). Optimal parameter combinations were established using multi-objective optimization, with protective efficacy carefully assessed from both head dynamic response and biomechanical response perspectives. The ideal P-TPMS liner possesses an outer protective layer thickness of 14.95 mm, a TPMS unit cell size of 12.23 mm, and a wall thickness of 3.93 mm. Compared to the traditional expanded polystyrene (EPS) liner, the optimized P-TPMS liner significantly reduces HIC (by ∼16%) and PLA (by ∼14%) while extending the impact duration. More critically, it transitions both intracranial pressure and brain tissue strain below their respective clinical injury thresholds, substantially lowering the risks of skull fracture and mild traumatic brain injury (mTBI). The P-TPMS construction facilitates continuous energy dissipation during impacts via incremental layer-by-layer buckling deformation, hence extending impact duration and markedly improving helmet protective efficacy. These findings offer theoretical foundations and technical direction for the creation of localized heterogeneous liner designs in advanced high-performance helmets, although the results are limited to frontal flat-anvil impact conditions.

To systematically investigate the protective effects of helmets against human head injuries under various shock wave conditions, a finite element head-helmet coupling model was developed. This model analyzed how helmets influence biomechanical response parameters, such as intracranial and cranial pressure, when subjected to a single blast wave and its accompanying shock wave. While extensive research exists on single blast scenarios, studies on the more complex and militarily relevant accompanying shock waves, which pose a greater threat due to prolonged loading and multiple reflections, remain scarce. Several impact scenarios were considered, including single frontal impact, positive continuous impacts, successive sidewall impacts, and simultaneous frontal and lateral impacts. The study examined the dynamic changes in brain tissue within a blast environment to assess the efficacy of helmets in protecting the human head. In single frontal impact scenarios, helmets effectively reduced intracranial pressures in the frontal, occipital, and parietal lobes by 32 %, 38 %, and 19 %, respectively, while significantly decreasing the stress peak at the back of the skull. During positive continuous impacts, helmets decreased intracranial pressure in the parietal and occipital lobes by 36 % and 21 %, respectively, although their effectiveness in reducing frontal lobe pressure was limited due to inadequate facial protection. For successive sidewall impacts, helmet protection delayed the blast wave, reducing intracranial pressure in the frontal lobe by 60 kPa but increasing pressure in the parietal lobe by 80 kPa. This alleviated stress on the skull's rear while increasing stress on the opposite side. In scenarios involving simultaneous frontal and lateral impacts, lateral blasts increased parietal intracranial pressure by 20 kPa, with the right hemisphere experiencing more pressure than the left due to the mitigating effect of reflective side blasts on skull stress. The study found that, compared to single blast waves, accompanying shock waves present a greater risk of cranial injuries due to their prolonged impact. These findings address a critical gap in blast neurotrauma research and provide valuable insights into the biomechanics of head injuries under realistic multi-blast conditions, which can directly inform the design of improved helmets with enhanced protection in complex blast environments. However, because shock waves may originate from multiple directions and elevations, the protective capability of conventional helmets for the facial region remains limited.

Helmets are crucial for protecting motorcycle riders from head injuries in accidents. This study proposes a helmet pad design based on a negative-Poisson’s-ratio (NPR) structure and comprehensively evaluates its protective effect on head injuries. A concave hexagonal honeycomb structure was embedded into the energy-absorbing lining of a motorcycle helmet, and finite element collision simulations were conducted according to the ECE R22.05 standard. These simulations compared and analyzed the differences in protective performance between concave hexagonal honeycomb helmets with different parameter configurations and traditional expanded polystyrene (EPS) helmets under flat anvil impact scenarios. Using biomechanical parameters, including peak linear acceleration (PLA), head injury criterion (HIC), intracranial pressure (ICP), maximum principal strain (MPS), and the probability of AIS2+ traumatic brain injury, the protective effect of the helmets on traumatic brain injury was evaluated. The results showed that when the wall angle of the honeycomb structure was 60°, honeycomb helmets with wall thicknesses of 0.8 mm and 1.0 mm significantly reduced PLA and HIC values. In particular, the honeycomb helmet with a wall thickness of 1.0 mm reduced ICP by 25.7%, while the honeycomb helmet with a wall thickness of 1.2 mm exhibited the lowest maximum principal strain in the skull compared to EPS helmets and reduced the probability of AIS2+ brain injury by 7.2%. Concave hexagonal honeycomb helmets demonstrated an excellent protective performance in reducing the risk of traumatic brain injury. These findings provide important theoretical foundations and engineering references for the design and optimization of new protective helmets.

The objective of this study was to mitigate the potential for head injury in motorcycle riders and enhance the protective properties of helmets. First, a finite element coupling model for evaluating helmet impact loads and deformation and their role in protecting the human head was developed and verified. Subsequently, inspired by the spider web structure with exceptional mechanical properties, two innovative and efficient liner structures were proposed and designed. Afterward, the new and improved liner structure was subjected to a rigorous, validated collision test, after which the kinematics and biomechanical parameters of the human head were obtained. These data were then used to conduct a comprehensive performance assessment of the new helmet, focusing on the risk of skull fracture and craniocerebral injury. Results showed that under the range of ballistic anvil crash test conditions, the helmet with an expanded polystyrene (EPS) + spider web structure decreased the head centroid acceleration significantly by 6 g and thus reduced the likelihood of skull fracture by 24

Traumatic brain injury (TBI) caused by explosions is the most common injury suffered by front-line soldiers. However, research on protective gear has primarily been limited to different types of helmets or their internal padding systems. Aerogels, with their microporous structures and high acoustic impedance properties, can effectively buffer the impact of explosions and generate significant acoustic mismatches between adjacent layers, making them promising materials for reducing the damage of blast shock waves to the head. This study aims to enhance the performance of protective equipment in mitigating explosion-induced head injuries and proposes a novel helmet mask structure based on polycarbonate and aerogel laminated composites. The coupled Eulerian-Lagrangian (CEL) method in Abaqus is employed to analyze the mechanical responses of different helmet-mask protective structures under blast shock waves through numerical simulation. The study emphasizes the influence of the type and thickness of the protective structure on head injury. Our findings indicate that a helmet with a face shield can significantly slow down the propagation of the blast wave to the face, thereby reducing craniocerebral injury. Further analysis reveals that the combination of polycarbonate and aerogel layers is more effective than a fully polycarbonate face shield in mitigating intracranial pressure (ICP) in the frontal and parietal regions. Additionally, masks with 3-layer configurations (featuring a single 0.6 mm thick aerogel layer) and 5-layer configurations (with double 0.6 mm thick aerogel layers) performed best in preventing moderate and severe traumatic brain injury (TBI). These results provide a scientific basis and a new direction for the design and optimization of future protective helmets.

The evaluation of damage tolerance in composite materials is essential for ensuring the safety of aircraft structures. One of the most challenging aspects of applying probability modeling-based methods to evaluate damage tolerance is determining the actual damage size distributions for in-service aircraft structures. Although existing nondeterministic approaches have been used to optimize inspection intervals of composite structures, few studies have investigated the effects of updates on the actual damage size distribution and its impact on both the probability of structural failure and inspection intervals. This paper proposes a dynamic optimization method for inspection intervals of composite structures based on Bayesian updating. The damage size distribution of the composite structure is characterized by a general stochastic distribution. A Bayesian updating methodology is presented to iteratively update the actual damage size distribution whenever new data becomes available. Based on the constructed probability model, the inspection intervals of composite structures are determined under the objectives of optimal safety and economy for civil aircraft using a Monte Carlo approach. Compared to prior distribution models, the proposed method achieves higher safety for structures during a single inspection, reduces the failure probability of structures throughout their entire service life, and incurs lower maintenance costs. It also enables maintenance personnel to flexibly adjust inspection intervals while facilitating quantitative evaluation of both failure probabilities and maintenance costs associated with these intervals. These findings suggest that the proposed method holds great potential in enabling maintenance personnel to make informed decisions regarding inspection intervals for improved safety and economic performance.

Detection and repair of composite damage is crucial to ensure the safety and reliability of aircraft structures. A novel approach to quantitatively evaluate the repair tolerance of composite structures in civil aircraft based on Bayesian updating is presented. The method incorporates historical damage inspection data to determine the prior distribution of damage size, which is then updated with newly collected damage size data using Bayesian theory. Monte Carlo simulation is employed to investigate the probability of failure and estimate maintenance costs, considering various factors such as the frequency and timing of damage events, damage detection, structural strength, gust loads, and maintenance expenses throughout the lifecycle of composite structures. Safety and economic factors are considered to establish a lower threshold for repairs and an upper threshold for maintenance based on the occurrence of accidental impact damage. Verification of the effectiveness and feasibility of a quantitative assessment method for repair tolerance is conducted using damage statistics data from civil aircraft routes utilizing the structural skin panels of composite outer wing. The results demonstrate that the method proposed in conjunction with extensive simulations and full utilization of field damage inspection data can effectively simulate unexpected impact damage situations that may occur during civil aircraft service and evaluate the reliability and economic feasibility of the repair of structure. The research findings hold significant theoretical and practical value for the preparation of documents for continued airworthiness of composite structures, including structural repair manuals and maintenance programs.

Through the analysis of the adhesion between the tooth head and axial clearance leakage attributed to vortex tooth shape deformation, an innovative tooth shape design concept has been introduced entitled “progressive change tooth high vortex tooth”. This unique design includes a gradual change in tooth height and an elevated vortex tooth profile, using temperature-sensitive materials to enhance the resolution of temperature loading on the vortex disc. By refining the process of resolving the temperature loading on the vortex disc, the mean temperature function of the fluid domain along the wall of the vortex tooth is calculated, and a steady-state temperature distribution model for the solid domain of the vortex tooth is formulated. Subsequently, a finite element model for the high eddy current disc is constructed using Abaqus 2021 finite element software, which facilitates the calculation of stress–strain distribution within the high eddy current disc under both gas pressure and temperature field loads. The results show that, especially under conditions of low speed and low exhaust pressure, the temperature load mainly influences the maximum deformation and stress distribution of the vortex tooth. Specifically, under the influence of heat-solid coupling, the maximum deformation of the progressive change tooth high vortex tooth occurs in close proximity to the central compression cavity, reaching up to 13 microns. These results provide a crucial theoretical basis for the structural design and performance optimization of the compressor.

In order to solve the problem of imbalance of internal forces in the system caused by the gravity force of the eccentric wheel and the orbiting scroll close to the drive bearing and the rotational inertia force during the operation of the electric scroll compressor, a dynamic model of the rotor system of the scroll compressor that takes into account the effect of the gas force was established using the multibody dynamics software ADAMS/View 2020. Dynamic simulation analysis of the rotor system is carried out, focusing on the force of the drive bearing; a parametric optimization method is adopted to optimize the position of the center-of-mass coordinates of the eccentric wheel of the relevant components, and the relevant parameters are derived after optimization. The results show that by adjusting the center-of-mass position of the eccentric wheel it is possible to optimize the unbalance force and unbalance moment of the main shaft drive system; compared with the pre-optimization, the force fluctuation ranges of the drive bearing in the horizontal and vertical directions are reduced, the peak value is reduced by 18%, and the impact force of the drive bearing during the initial period of compressor operation is effectively relieved. Through optimization calculation, the vibration and noise of the system are reduced, the operating stability of the scroll compressor is improved, and analytical methods and theoretical guidance are provided for the design and prediction of the dynamic behavior of the scroll compressors.

Helmets play a crucial role in protecting motorcycle riders during two-wheeler accidents by reducing the risk of head injuries. This study investigated the complex interplay between the density, Poisson's ratio, and Young's modulus of a helmet liner and their impact on biomechanical factors contributing to traumatic brain injury during collisions. A validated finite element model of a 50th percentile detailed human head was initially used, followed by the development of a coupled helmet head model for collision simulations. The accuracy of the model was assessed by comparing the center-of-mass acceleration data of the head with the experimental results. This study analyzed the von Mises stress, skull stress, and intracranial pressure (ICP),and the results revealed patterns in stress distribution and the potential for cranial and brain injuries. Stress concentrations were observed in the cervical region before the impact, characterized by compressive stress on the impacted side and tensile stress on the opposite side, with peak stress levels found in the temporal bone base and frontal bone. After the impact, brain inertia-driven movements can further increase the risk of traumatic brain injury. The study found a positive correlation between liner density and center-of-mass acceleration of the head in the absence of bottoming out of the liner. By optimizing the liner properties, the study achieved a 4.5% reduction in head acceleration, a 10.1% decrease in skull stress, and a 19.8% reduction in ICP. These findings offer valuable insights for biomechanical research on head injuries caused by traffic accidents and for improving helmet designs to enhance protective measures.

The air conditioning compressor is a critical component in automobile heating, ventilation and air conditioning systems. However, compressor noise has long been a problem for automobile manufacturers. In recent years, the development and application of automobile air conditioning scroll compressors has increased significantly due to their low mechanical vibration and noise. However, their limitations in terms of airflow pulse and noise cannot be ignored, especially in low speed and high load conditions where the noise generated has a negative impact on driving and passenger experience. Noise and airflow pulses are important considerations that cannot be ignored. This study innovatively modifies the end cap structure of the scroll compressor, using the principles of expansion muffler and insertion tube structure, with the aim of improving the acoustic quality of the scroll compressor. The results show that the novel valve construction can significantly reduce the sound pressure level of the scroll compressor noise to a maximum of 75.20 dBA. The results of this study provide a theoretical basis and practical technical applications for future research and development in the automobile industry.

The gear shaft is prone to failure in extremely harsh operating environment, it is of importance to implement fault diagnosis to ensure the healthy running of the equipment. In this paper, the early abnormal detection method of gear shaft is investigated. Time synchronous averaging (TSA) algorithms were used to remove noise from the original vibration signals and reduce the huge amount of data, and autoregressive (AR) model was employed to calculate residual errors. The fault feature parameters of residual were extracted to preliminarily detect gear faults. Discrete wavelet transform (DWT) was implemented to further reduce the noise. The results show that the failure of the fifth file can be detected. It is verified that the proposed method can detect the fault of the gear shaft more effectively by using DWT and AR model, which provides a theoretical basis for the engineering application of key equipment.

In order to analyze the dynamic responses of rails subjected to distributed moving electromagnetic pressure, the vibration governing equations of rails on viscoelastic support were established based on Winkler foundation beam model. The analytical expression of the vibration response of the rail was deduced by modal superposition method. Taking a typical current excitation as an example, the dynamic responses (such as vibration deflection, velocity, bending stress, and so on) were calculated, and the characteristics along with the critical velocity effects were emphatically analyzed. The influence of support stiffness and damping on the dynamic response of rails were also investigated. The research results can provide a theoretical basis for the design of launcher packaging structure.

The free vibration of rotating functionally graded nanobeams under different boundary conditions is studied based on nonlocal elasticity theory within the framework of Euler-Bernoulli and Timoshenko beam theories. The thickness-wise material gradient variation of the nanobeam is considered. By introducing a second-order axial shortening term into the displacement field, the governing equations of motion of the present new nonlocal model of rotating nanobeams are derived by the Hamilton's principle. The nonlocal differential equations are solved through the Galerkin method. The present nonlocal models are validated through the convergence and comparison studies. Numerical results are presented to investigate the influences of the nonlocal parameter, angular velocity, material gradient variation together with slenderness ratio on the vibration of rotating FG nanobeams with different boundary conditions. Totally different from stationary nanobeams, the rotating nanobeams with relatively high angular velocity could produce larger fundamental frequencies than local counterparts. Additionally, the axial stretching-transverse bending coupled vibration is perfectly shown through the frequency loci veering and modal conversion.

In order to predict and evaluate injury mechanism and biomechanical response of the facial impact on head injury in a crash accident. With the combined modern medical imaging technologies, namely computed tomography (CT) and magnetic resonance imaging (MRI), both geometric and finite element (FE) models for human head-neck with detailed cranio-facial structure were developed. The cadaveric head impact tests were conducted to validate the headneck finite element model. The intracranial pressure, skull dynamic response and skull-brain relative displacement of the whole head-neck model were compared with experimental data. Nine typical cases of facial traffic accidents were simulated, with the individual stress wave propagation paths to the intracranial contents through the facial and cranial skeleton being discussed thoroughly. Intracranial pressure, von Mises stress and shear stress distribution were achieved. It is proved that facial structure dissipates a large amount of impact energy to protect the brain in its most natural way. The propagation path and distribution of stress wave in the skull and brain determine the mechanism of brain impact injury, which provides a theoretic basis for the diagnosis, treatment and protection of craniocerebral injury caused by facial impact.

Aiming at the uncertainty of material parameters of human brain tissue, the influence of tissue material performance sensitivity on frequency and mode shape under free vibration is studied. In this paper, the 50th percentile finite element (FE) model of human head and neck with detailed anatomical characteristics has been chosen as the research object, the parameters of skull, cerebrospinal fluid (CSF) and brain tissue materials with high sensitivity are analyzed by orthogonal test design and variance analysis. The results show that the natural frequencies of Group 7, Group 8 and Group 9 are all around 230[Formula: see text]Hz, which are basically consistent with the initial parameter of 229.18[Formula: see text]Hz, and the intracranial displacements of the three groups are also concentrated on the lateral nasal cartilage. The main reason is that the Young’s modulus of the skull used in three groups of experiments is 9780[Formula: see text]Mpa, which is close to the initial parameter of 8000[Formula: see text]Mpa. It indicates that the material parameter of the skull has the greatest influence on the dynamic characteristics of human head and neck, followed by the CSF and brain tissue. This study provides an effective method for vehicle safety and head and neck injury protection, and supplies a reference for FE analysis of head collision damage.

This work aims at predicting and evaluating the biomechanical response of the facial impact on head injury in a crash accident. With the combination of CT/MRI medical imaging technique, the 50th percentile head biomechanical model with detailed cranio-facial structure is established. After which the validity of the model based on the classical experimental data from Nahum and Trosseille is verified. The model consists of 327,536 nodes and 1,337,903 units, and it has good biological fidelity. Based on the analysis of nine typical cases of facial traffic accidents, this work studies the propagation path of stress wave in the skull, then brain, von Mises stress and shear stress distribution are achieved. It is proved that facial structure can absorb a large amount of impact energy to protect the brain. The propagation path and distribution of stress wave in the skull and brain determine the mechanism of brain impact injury, which provides a theoretic basis for the diagnosis, treatment and protection of craniocerebral injury caused by facial impact.

In this paper, a method of modeling and simulatingflexible beam finite rotation is investigated. Based on theassumptions of low speed and small deformation, theANCF method is regarded as a finite element interpolationmethod to obtain the constant mass matrix of the flexiblebeam; the local coordinate system in the ANCF method isconsidered the floating coordinate system, and thestiffness matrix independent of the generalizedcoordinates is obtained. The split-iteration method is usedto expand the generalized coordinates that are notcontained in the constraint equations to the 2nd -orderTaylor series of the generalized coordinates that arecontained in the constraint equations and the Lagrangemultipliers. The nonlinear constraint equations arelinearized to the 1st -order Taylor series of the generalizedcoordinates. Then, the generalized coordinates andLagrange multipliers can be solved quickly. The resultsshow that the dynamic equations can be effectivelysimplified by combining the ANCF method with the FFRmethod for the small-deformation problems. Thelow-order Taylor approximation of generalizedcoordinates in both the dynamic equations and constrainedequations does not lose substantial computationalaccuracy but can significantly reduce computational time.The results of this investigation have important referencevalues for dynamic analysis of cranes, aerial workplatforms, and other engineering equipment. DOI: http://dx.doi.org/10.5755/j01.mech.24.5.20358

头颈部外骨骼系统是一种为虚拟现实交互设备-头盔显示器提供主动控制的系统.而该系统执行机构-6URHS平台的动力学特性是否能满足头部运动的要求,将会直接影响到整个系统的使用效果.针对执行机构结构的特殊性,建立了动力学模型,分析了影响外骨骼系统动力学特性的主要影响因素,设计了动平台质量等6因素3水平共18组正交试验,利用极差分析法对影响因素进行了定量比较分析.结果表明外筒惯量对6URHS并联平台的动力学特性影响最为明显,而外筒质量与外筒惯量的极差和比小于1/8,其对6URHS并联平台的影响最弱.

Vehicle detection and type recognition based on static images is highly practical and directly applicable for various operations in a traffic surveillance system. This paper will introduce the processing of automatic vehicle detection and recognition. First, Haar-like features and AdaBoost algorithms are applied for feature extracting and constructing classifiers, which are used to locate the vehicle over the input image. Then, the Gabor wavelet transform and a local binary pattern operator is used to extract multi-scale and multi-orientation vehicle features, according to the outside interference on the image and the random position of the vehicle. Finally, the image is divided into small regions, from which histograms sequences are extracted and concentrated to represent the vehicle features. Principal component analysis is adopted to reach a low dimensional histogram feature, which is used to measure the similarity of different vehicles in euler space and the nearest neighborhood is exploited for final classification. The typed experiment shows that our detection rate is over 97 %, with a false rate of only 3 %, and that the vehicle recognition rate is over 91 %, while maintaining a fast processing time. This exhibits promising potential for implementation with real-world applications.