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The existing quantitative (such as fractal dimension) methods for the dynamic performance of magnetorheological (MR) damping systems have problems in predicting damping efficiency due to the small sample size, overfitting risk, poor generalization and robustness, and difficulty in meeting industrial reliability requirements. In order to improve the prediction accuracy of damping efficiency in MR damping systems, ensure the reliability of prediction results for small sample datasets, this study first calculates five entropy indices – Approximate Entropy (ApEn), Sample Entropy (SampEn), Permutation Entropy (PermEn), Fuzzy Entropy (FuzzyEn), and Shannon Entropy (ShannonEn) – of the system’s time series under different operating states. These indicators are used to accurately evaluate the dynamic performance of the system and determine parameters that quantify its dynamic quality. Taking damping efficiency as the prediction objective, each entropy index is treated as a single input parameter, and a cross validation generalized regression neural network (GRNN) model is adopted to select the optimal entropy calculation parameter from the comprehensive score evaluation prediction results. On this basis, the entropy feature vector was reconstructed, and a reconstruction entropy feature prediction algorithm based on GRNN and balance criterion was established. The performance of the model was compared with existing prediction algorithms, and the performance of the optimal combination was verified. The industrial environment was simulated, and the industrial application prospects of the model were evaluated. Key findings indicate that: The preferred single entropy parameter using GRNN can achieve a prediction accuracy of 99 %, which is suitable for quantifying the dynamic quality of the system. Among all single entropy parameters, approximate entropy(ApEn) exhibits the highest prediction accuracy; The comprehensive scoring method based on GRNN Gaussian kernel selects the optimal parameter scheme for single entropy calculation; The reconstructed entropy feature vector was used to select the optimal entropy feature combination scheme for damping efficiency prediction based on GRNN inverse multiple quadratic (IMQ)-kernel and balance criterion; The combination of “ApEn+FuzzyEn” GRNN IMQ-kernel and balance criterion not only achieves better prediction accuracy than existing VMD-box dimension-GRNN, Long Short-Term Memory (LSTM), Random Forest (RF), and Support Vector Machine (SVM), but also demonstrates good generalization, robustness and reliability, as well as stable performance under different SNR noises. The relevant algorithms have also achieved good prediction accuracy and generalization in other datasets. This research model algorithm breaks through the accuracy bottleneck of traditional fractal dimension methods and provides an efficient, stable, and reliable prediction solution for small sample datasets. Its industrial application prospects are broad.

In the event that a floating drilling platform is struck suddenly by a typhoon, preventing the complete retrieval of the riser, a compensation system is required to alleviate the considerable dynamic loads on the riser resulting from platform movement, thus keeping the riser tension within safe limits. Evaluation of the mathematical model for the conventional vibration isolation system indicated unsatisfactory performance under conditions of large displacement and ultra-low-frequency vibration. To address this, a new dynamic load compensation system for the riser has been developed, along with a dedicated experimental platform. In this setup, platform heave is simulated via the extension and retraction of a hydraulic cylinder, while the riser load is represented using multiple mass blocks. The experimental platform supports both manual and automatic control modes. Utilizing Visual Basic (VB) programming integrated with an Access database, the monitoring and control software provides capabilities for parameter configuration, data monitoring, and data archiving. Experiments performed on this platform, including heavy simulation and dynamic load compensation, demonstrated a compensation effect of 27.4 %. The successful mitigation of dynamic loads on the riser presents a novel approach for drilling platforms to cope with typhoon emergencies and suggests valuable applications for vibration isolation technology in other domains.

Identifying seismic disaster precursors and instability early warning signs in tunnels is critical for seismic design and catastrophe warning. Current approaches predominantly rely on static assessments of specific states, either post-event or at peak response. Thus, they fail to capture the continuous evolution and abrupt transitions inherent in nonlinear dynamic systems. For this purpose, the Load/Unload Response Ratio (LURR) theory was introduced to evaluate the seismic stability of tunnels. Definitions were established for loading and unloading parameters, response parameters, and the LURR during the seismic response of tunnels. According to the principles of the LURR theory, shaking table model tests were performed on an unlined tunnel to study how the LURR varies and how the soil’s stability changes with different seismic intensities. Research shows that as seismic amplitude increases, the stability of an unlined tunnel evolves through three distinct phases: stable bearing capacity, localized collapse, and overall collapse. A correlation is observed between the time-history curve of the LURR of the surrounding soil and the progression of stability. During the stable bearing phase, LURR values fluctuate at low magnitudes, while the maximum LURR at the weakest structural location (the arch foot) gradually rises with increasing seismic amplitude. As stability deteriorates, the LURR displays a localized growth pattern in the crown and sidewall regions (monitoring points 1-4). A declining trend in the regional LURR peak value corresponds to the onset of localized collapse in that specific area. Following the initial localized collapse, the maximum LURR shifts from the crown zone to the sidewall foot and invert waist areas. When the regional peak LURR in this secondary zone begins to decrease, the tunnel experiences overall collapse that propagates to the ground surface. Based on shaking table model test results, the decline of the first localized LURR peak, combined with its spatial migration, can serve as a criterion for assessing localized tunnel instability. Furthermore, the decline of two or more localized LURR peaks provides a predictive indicator for the overall instability of the tunnel.

The excavation of complex deep foundation pit poses significant risks to the safety of adjacent existing structures. To investigate the force and deformation characteristics of deep foundation pit, this study focuses on the pile-anchor support system of a deep foundation pit for a third-line ship lock on the Xiangjiang River. Model tests and numerical modeling analyses were conducted to evaluate the influence of pile diameters (1.0 m ≤d≤ 2.0 m) on the force and deformation characteristics of pile-anchor support system in deep foundation pit adjacent to buildings. The results indicate the following: (1) The variation pattern of horizontal displacement at the top of pile in the model test is consistent with that observed in the numerical simulation. The bending moment of the pile body exhibits an “S”-shaped distribution, confirming the reliability of numerical model. (2) The horizontal displacement curve of pile body presents a “bulging belly” shape, with smaller displacements at the top and bottom and larger displacements in the middle. The curvature of displacement decreases as the pile diameter increases. (3) Larger pile diameters result in greater bending moments in the pile body, smaller changes in the positions of positive and negative bending moment extremes, and reduced surface settlement. (4) The uplift at the bottom of foundation pit initially decreases and then increases, forming a “hooked” curve. The influence of pile diameter on bottom uplift is relatively minor. (5) Larger pile diameters promote a transition in the active failure mode from semi-infinite soil to finite soil, with d= 1.5 m serving as the critical value for finite soil conditions. (6) Based on economic considerations, d= 1.5 m is determined to be the optimal pile diameter. (7) The active deformation sliding surface of finite soil behind piles is a curve or polyline that is higher than the heel of wall and returns to the adjacent buildings. This study provides valuable experimental data for investigating finite soil deformation behind piles in the pile-anchor support system for deep foundation pit, offering both theoretical significance and practical engineering value.

Under the premise of ensuring modal and strength characteristics, achieving lightweight design of the structure simultaneously has become a key issue of concern for major automobile manufacturers and research institutions. To reduce the mass redundancy of the bus chassis frame, save production costs and energy consumption, a multi-objective optimization scheme based on surrogate model technology was proposed, which could maximize weight reduction without reducing the natural frequency or increasing the peak stress. According to the working principle, load characteristics and composition of the chassis frame, a parametric coupling model for modal and strength was constructed, and the stress, deformation, natural frequency and vibration mode characteristics of the overall structure were obtained. The dimensions of H-steel were determined as design variables, and the discrete mapping data sets of maximum stress, first-order natural frequency and mass were obtained through the Latin square design scheme. Parameters such as the coefficient of determination, adjusted coefficient of determination and root mean square error were selected as the standard evaluation indicators for the accuracy of the response surface model. The reliability of different surrogate models was compared and analyzed, and finally the Kriging model was adopted as the approximation function in the construction of the mathematical model. An optimized mathematical model was constructed to convert the modal and strength objectives into boundary conditions. The design variables meeting the optimization objectives were derived through the sequential quadratic programming algorithm. The results showed that, without reducing the requirements for strength and stiffness indicators, this optimization scheme could reduce the weight of the chassis frame by 9.94 %, which has good economic benefits and engineering value.

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.

In order to promote the resource utilization of the byproducts of municipal solid waste incineration in asphalt pavement materials, this study selected different types of waste incineration fly ash as fillers and prepared waste fly ash-asphalt mastic materials. The Brookfield viscosity test was used to investigate the variation in apparent viscosity of the waste fly ash-asphalt mastic at different temperatures. The dynamic shear rheological test was employed to study the effects of fly ash content on the viscoelastic properties of asphalt under different frequencies. The low-temperature bending beam rheological test was used to analyze the changes in creep stiffness and creep rate of the waste fly ash-asphalt mastic. Based on this, the rotating film oven aging test was conducted to investigate the mass loss and softening point increment of the waste fly ash-asphalt mastic. The results indicated that the small particle size and developed pore structure of fly ash contributed to the adsorption of asphalt components, enhancing the volume of the mastic. As the fly ash content increased, its specific surface area also increased, further promoting the increase in the viscosity of the asphalt mastic. Under low-temperature conditions, the asphalt mastic became more prone to hardening and brittleness, which resulted in poorer low-temperature cracking resistance, consistent with the ductility results.

This paper presents a co-simulation of MATLAB and CarSim to control and model a vehicle suspension system under different road surface conditions, either wet or dry, using an active fuzzy controller in MATLAB. CarSim is a professional vehicle simulation software capable of modeling nonlinear car dynamics with various uncertainties. These uncertainties are addressed by the fuzzy set approach due to its qualitative and robust control capabilities, effectively handling noise, disturbances (such as road conditions), and unknown parameters in CarSim’s vehicle model. The design of an active steering controller and rotational torque system using a fuzzy controller is crucial for enhancing road safety, especially given the increasing number of vehicle crashes. The research methodology varies based on the study's purpose, nature, and implementation capabilities. Accordingly, this research focuses on designing an integrated controller for an active four-wheel-drive system and direct rotary torque control using a fuzzy control method in the MATLAB Simulink environment. This study is analytical and functional, utilizing CarSim for simulation. A fuzzy logic-based integrated control system was designed for steady-state control to improve vehicle stability and steering. The controller adjusts the steering angle and torque to regulate the vehicle’s angular velocity and slip angle under various conditions. As tire performance changes during different maneuvers, the controller dynamically adapts its output to maintain optimal operation within the effective performance range. The significance of using fuzzy logic lies in its ability to handle non-linearity without requiring approximation, ensuring high accuracy. Additionally, it delivers excellent results in enhancing vehicle stability. The findings indicate that the controller significantly improves the vehicle’s dynamic behavior across different driving maneuvers compared to an uncontrolled vehicle.