High Speed Research Articles

Performance Evaluation of 2G HTS Current Leads for HTS Transformers on High Speed Rail

Performance Evaluation of 2G HTS Current Leads for HTS Transformers on High Speed Rail

Experimental study on the residual life of high speed trains axles considering initial defects

Experimental study on the residual life of high speed trains axles considering initial defects

High speed impact induced dehydrogenation of titanium hydride and formation of cellular structure via cold spray

In this study, it is revealed for the first time that ultra-high-speed impact can trigger in-situ dehydrogenation at the impact interface of titanium hydride (TiH). This phenomenon leads to a phase transformation from brittle TiH to ductile Ti, causing a shift in the ductile-to-brittle transition from the impact interface to the particle interior. Inspired by this unique behavior, and considering the mechanical interactions between particles during the spray process, TiH powders were used as feedstock to successfully produce a large-scale random cellular structure through cold spray. A systematic investigation of the deposition process revealed that unbroken TiH particles interact with dehydrogenated ones, resulting in only the ductile portion of the TiH particle being deposited, while the brittle interior is spalled off, consequently forming the “walls” of the cellular structures. This work highlights the potential of TiH powders to advance cold spray technology, particularly in the creation of complex cellular structures.

A review on high speed micro-milling of shape memory alloy (NiTinol): process and post perspective

A review on high speed micro-milling of shape memory alloy (NiTinol): process and post perspective

Synthesis of a lightweight and dual-band (K and Ka-band) microwave absorber based on cobalt ferrite/mesoporous carbon nanocomposite for stealth technology

Mesoporous carbon has gained significant attention as microwave absorber owing to its lightweight, high surface area and dielectric loss. Herein, for better impedance matching, CoFe2O4/mesoporous-carbon hybrid nanocomposites were synthesized with different content of mesoporous-carbon via a facile hydrothermal method and systematically investigated their K and Ka-band microwave absorption properties. RAMAN analysis establishes the strong interaction amid CoFe2O4 and mesoporous-carbon. Magnetic study confirmed the ferromagnetic nature of the nanocomposite which is helpful for high frequency range absorbers. The CoFe2O4/MC-60 nanocomposite presents a reflection loss of −51 dB at 2.5 mm thickness with an effective absorption bandwidth of 4.2 GHz. The |Zin/Z0| value for this hybrid nanocomposite was closer to 1. The superb absorption properties can be ascribed to best impedance matching and the synergistic effect of the heterogeneous interfaces between CoFe2O4 nanoparticles and carbon. This work can advance the development of magnetic/carbon absorber for high speed communication and military fields.

Pseudo random bit generator in QCA for high speed communications

Quantum-dot cellular automata (QCA) technology is another new technology in the field of nanoelectronics and quantum. With the help of this technology, basic to advanced digital circuits can be designed and implemented with low energy consumption and small area. Therefore, in this paper, a new design for a four- and eight-bit Linear feedback shift register (LFSR) or random counter, as well as a rising-edge-sensitive D flip-flop with the least possible number of cells and the smallest area, was presented. This paper first designs the proposed D flip-flop with 24 cells and an area of 0.01μm2, so that with the help of this flip-flop it can design four and eight-bit LFSR. This flip-flop is one of the most optimal and suitable designs in terms of area and number of cells. Then, in the second step, a four-bit LFSR with 144 cells and an area of 0.2μm2 was designed with the help of the proposed flip-flop in the most optimal possible state. Also, in the third step, an eight-bit LFSR with 281 cells and an area of 0.4μm2 has been implemented for the first time in QCA technology, which is among the best possible designs. All the designs and simulations of this article were done in QCADesigner version 2.0.3 software and with QCAPro software, the energy consumption of the proposed circuits.

Hypersonic glide vehicle trajectory prediction based on frequency enhanced channel attention and light sampling-oriented MLP network

Hypersonic Glide Vehicles (HGVs) are advanced aircraft that can achieve extremely high speeds (generally over 5 Mach) and maneuverability within the Earth's atmosphere. HGV trajectory prediction is crucial for effective defense planning and interception strategies. In recent years, HGV trajectory prediction methods based on deep learning have the great potential to significantly enhance prediction accuracy and efficiency. However, it's still challenging to strike a balance between improving prediction performance and reducing computation costs of the deep learning trajectory prediction models. To solve this problem, we propose a new deep learning framework (FECA-LSMN) for efficient HGV trajectory prediction. The model first uses a Frequency Enhanced Channel Attention (FECA) module to facilitate the fusion of different HGV trajectory features, and then subsequently employs a Light Sampling-oriented Multi-Layer Perceptron Network (LSMN) based on simple MLP-based structures to extract long/short-term HGV trajectory features for accurate trajectory prediction. Also, we employ a new data normalization method called reversible instance normalization (RevIN) to enhance the prediction accuracy and training stability of the network. Compared to other popular trajectory prediction models based on LSTM, GRU and Transformer, our FECA-LSMN model achieves leading or comparable performance in terms of RMSE, MAE and MAPE metrics while demonstrating notably faster computation time. The ablation experiments show that the incorporation of the FECA module significantly improves the prediction performance of the network. The RevIN data normalization technique outperforms traditional min-max normalization as well.

Impact of Short-Haul High Speed Rail Commuting on Land Use and Spatial Structure in a Multi-Centre Metropolitan Area

Owing to the enhanced accessibility afforded by high-speed rail, the relationship between megacities and their neighboring cities has grown closer. Megacities exert a significant influence on the land use of neighboring cities. This study employs a spatial econometric model to investigate the direct impact and spatial spillover effects of high-speed rail on urban land values, based on urban panel data from China’s Yangtze River Delta region (2006-2020). The results revealed that shorter commuting times and improved frequency of service had a more substantial effect. Additionally, due to alterations in land values, there is a distinct preference tendency for urban land use attributes. Therefore, the city’s spatial organization has transformed, and its center of gravity has shifted as well. This study provides crucial theoretical justifications and empirical evidence to fill the gaps left by previous research on the effects of short-haul high-speed rail commuting on urban housing prices and land use. The study also offers valuable insights for strategic planning and implementation aimed at promoting urban development and urban agglomeration construction through HSR construction.

Longitudinal and Lateral Cooperative Control of Preview Intelligent Vehicles with Stabilization

Aiming at the highly nonlinear and coupled longitudinal and transverse motion control problems of intelligent vehicle path tracking control, a new method of preview MPC path tracking control is proposed by combining visual preview model and model predictive control theory. The method first locally linearizes the nonlinear prediction model and transforms the MPC optimization solution problem into a quadratic programming problem. The longitudinal vehicle speed and the preview distance are then treated as known in each control time domain, an exponential model is applied to characterize the longitudinal vehicle speed, and a transverse angular velocity-center of mass lateral deflection (r-β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$r-\\beta $$\\end{document}) phase plane plot is applied to characterize the vehicle stability. Finally, proportional integral differential stability controller is designed to improve vehicle stability. Simulation and test results show that: Compared with the MPC tracking control method, the preview MPC control method proposed in this paper can optimize the vehicle tracking performance on different adhesion coefficient road surfaces and improve the tracking accuracy, and this enhancement effect is more obvious at high speeds.

Development and Verification of a Multi-Physics Transport Code of Molten Salt Reactor Fission Products

The transport of fission products in molten salt reactors has attracted much attention. However, few codes can completely describe the transport characteristic, though the migration of fission products in the molten salt reactor is essential to estimate the source term, decay heat, and radiation shielding. This study built a program named ThorFPMC (Thorium Fission Products Migration Code) that can handle the multi-physics transport characteristic based on the flow burnup code ThorMODEc (Thorium MOlten Salt Reactor Specific DEpletion Code). A problem-related depletion chain compression method was applied to decrease the order of the solve matrix. The matrix exponential and splitting methods were applied to solve the steady state and transient calculation, respectively. Error analysis showed that for a specific problem, the simplified depletion chain matrix index method could solve the fission products migration equation with an arbitrary time-step with high speed (s) and high precision (10−4); the splitting method could reach a precision of 10−2 level for the full fuel depletion chain, multi-nodes, and transient problems. Compared to the Strang splitting method, the perturbation splitting method has higher precision and less time consumption. In summary, the developed programmer could describe the migration effect of fission products in molten salt reactors, which provides a significant tool for the design of molten salt reactors.

The influence of menstrual cycle phase on isokinetic knee flexor and extensor strength in female soccer players: a pilot study

ABSTRACT The prevalence of anterior cruciate ligament injury in female soccer players has been attributed to hormonal fluctuations during the menstrual cycle (MC), with injury incidence greatest during the follicular phase. Eight, eumenorrheic, collegiate soccer players (19.5 ± 0.75 years, 1.62 ± 4.90 cm, 61.12 ± 7.6 kg mean ± SD) completed eccentric knee flexor and concentric knee extensor trials at 60 and 240°·s−1 during the follicular, ovulation and luteal phases of their MC. Peak torque and corresponding angle of peak torque were maintained across all phases of the MC, irrespective of testing modality and speed (p ≥ 0.149). Strength ratios defined using peak torque were also not sensitive to MC phase (p ≥ 0.933). However, Functional Range in eccentric knee flexion was significantly lower during the follicular phase (p = 0.017), at both testing speeds. This supports epidemiological observations but highlights the importance of analysing isokinetic data beyond the peak of the strength curve. Interpretation of isokinetic data should therefore focus on points of “weakness” as opposed to maximum strength, whilst (p)rehabilitative strategies should consider strength through range of motion, and at different speeds. Eccentric hamstring strength was observed to decrease significantly at the higher speed, contrary to observations in elite male players, and potentially reflecting a differential training adaptation.

Automated production of batched unclonable micro-patterns anti-counterfeiting labels with strong robustness and rapid recognition speed

Anti-counterfeiting technologies are indeed crucial for information security and protecting product authenticity. Traditional anti-counterfeiting methods have their limitations due to their clonable nature. Exploring new technologies, particularly those based on pixel-level textures, is a promising avenue to address the clonable issue due to high encoding capacity. However, research in this field is still in its early stages. This work introduces a new fluorescent anti-counterfeiting label technology with four key characteristics: efficient laser etching, high-throughput fabrication and segmentation, robustness aided by data augmentation, and an exceptionally high recognition speed. Specifically, the etching achieves a speed of 1,200 labels/3s, the high-throughput procedures yield a rate of 2,400 labels/4 mins, and the total count is about 5.2 × 104 labels. The number of labels is further augmented to about 5.2 × 106 by implementing arbitrary rotation and brightness variation to enhance the robustness in the recognition procedure. We divide these labels into 44 categories based on differences in patterns. Utilizing machine learning methods, we have achieved a total recognition (including extraction and search process) time per label averaging 421.96 ms without classification, and 40.13 ms with classification. Specifically, the search process with classification is nearly fiftieth times shorter than the non-classification method, reaching 8.52 ms in average. The overall recognition time is much faster than previous works, and achieves an accuracy of over 98.7%. This work significantly increases the practical significance of pixel-level anti-counterfeiting labels.

Synchronized Multi-Laser Powder Bed Fusion (M-LPBF) Additive Manufacturing: A Technique for Controlling the Microstructure of Ti–6Al–4V

One of the technological hurdles in the widespread application of additive manufacturing is the formation of undesired microstructure and defects, e.g., the formation of columnar grains in Ti-6Al-4V—the columnar microstructure results in anisotropic mechanical properties, a reduction in ductility, and a decrease in the endurance limit. Here, we present the potential implementation of a hexagonal array of synchronized lasers to alter the microstructure of Ti–6Al–4V toward the formation of preferable equiaxed grains. An anisotropic heat transfer model is employed to obtain the temporal/spatial temperature distributions and construct the solidification map for various process parameters, i.e., laser power, scanning speed, and the internal distance among lasers in the array. Approximately 55% of the volume fraction of equiaxed grains is obtained using a laser power of P = 500 W and a scanning speed of v = 100 mm/s. The volume fraction of the equiaxed grains decreases with increasing scanning velocity; it drops to 38% for v = 1000 mm/s. This reduction is attributed to the decrease in absorbed heat and thermal crosstalk among lasers, i.e., the absorbed heat is higher at low scanning speeds, promoting thermal crosstalk between melt pools and subsequently forming a large volume fraction of equiaxed grains. Additionally, a degree of overlap between lasers in the array is required for high scanning speeds (v = 1000 mm/s) to form a coherent melt pool, although this is unnecessary for low scanning speeds (v = 100 mm/s).

A self-regulated wind energy harvester with automatic mode transition strategy enabled by wind-induced centrifugal force

Abstract Natural wind energy distributes over a wide speed range, but conventional wind turbines with high electrical damping can only work under relatively high wind speeds, whereas breeze harvesters with low electrical damping suffer from limited electric outputs despite their low start-up wind speeds. To solve this dilemma, we report herein an automatic mode transition (AMT) strategy for rotary wind energy harvesters (WEHs) to realize self-regulation of electrical damping according to ambient wind speeds. The superior performance achieved with the AMT strategy has been demonstrated through an AMT-WEH comprising a low-damping as well as a high-damping power generation units. Theoretical analysis and experimental tests reveal that the AMT-WEH not only can work in low-damping single-unit mode to harvest weak wind (≥ 2.6 m/s), but also can switch spontaneously to high-damping dual-unit mode to efficiently capture strong wind. As connected with matched electrical loads, the AMT-WEH can switch to dual-unit mode and generate high average power of 188.2 mW under 8.2 m/s wind, which is more than 11.5-fold increase as compared with that (16.3 mW) of a conventional WEH without the AMT design. This study demonstrates a distinctive AMT strategy for WEHs to effectively exploit wide-speed-range wind energy toward self-contained sensors and electronics.

Method for Detecting Roadbed Compaction Degree Based on Machine Learning and Vibration Acceleration

Roadbed construction occupies a core position in highway construction, but its quality is easily constrained by multiple factors such as changing environmental factors, the performance of construction equipment, and the professional abilities of construction personnel, leading to potential quality risks. Traditional quality inspection methods are mostly carried out after construction is completed, making it difficult to achieve continuous and real-time monitoring of roadbed compaction quality, which to some extent limits the real-time feedback and adjustment of construction quality. Vibration compaction technology has been widely used in the field of highway engineering due to its high efficiency and speed. The compaction degree is directly related to the durability and service life of the highway; therefore, accurate and efficient detection of compaction degree is crucial. This article proposes a method for detecting roadbed compaction degree by integrating machine learning (ML) and vibration acceleration signals. This method aims to achieve accurate evaluation of roadbed compaction by real-time monitoring and analysis of vibration acceleration data, combined with the powerful prediction and classification capabilities of ML algorithms. The experimental results show that this method not only improves the detection efficiency, but also significantly enhances the accuracy of compaction degree detection.

Modeling Method of Meshing Stiffness of High Speed Spur Gears

As one of the most important dynamic excitation sources, the gear time-varying mesh stiffness is the key parameter of gear system dynamic model. So how to calculate the gear mesh stiffness accurately is of great importance. Based on Euler beam theory, this paper proposes a primitive calculation algorithm (PCA) to calculate the time-varying mesh stiffness of spur gears. A simplified gear model is developed based on nonlinear strain-displacement relationships, and a finite element program is used to simulate the gear's meshing stiffness. The rationality of this method was verified through finite element analysis. The results indicate that mesh stiffness plays a crucial role in controlling mesh deformation. In view of this, this study lays a theoretical foundation for further analysis of the vibration and noise of gears.

The Discovery of Accelerating Expansion of Universe 8.8 Billion Years after the Big Bang Vindicates M1 World One Out of the Six Solutions of Einstein’s General Theory of Relativity

This paper gives the mathematical methodology (Tensor mathematics) of describing the surfaces of our Universe in General Theory of Relativity. It expresses the mass energy equivalence formula. It introduces the concept of time dilation, length contraction and mass increment in high speed frame of reference. Minowski space time 4D manifold is illustrated for representing the flat spacetime fabric Reimannian Metric is enumerated. Schwarzschild metric and how mass is accounted for is given.

On the Influence of Welding Parameters and Their Interdependence During Robotic Continuous Ultrasonic Welding of Carbon Fibre Reinforced Thermoplastics.

Ultrasonic welding of fibre-reinforced thermoplastics is a joining technology with high potential for short welding times and low energy consumption. While the majority of the current studies on continuous ultrasonic welding have so far focused on woven reinforcements, unidirectional materials are preferred for highly loaded aerospace components due to their better mechanical performance. Therefore, this paper investigates the influence and interdependence of the welding speed, amplitude, and energy director thickness on the weld quality of adherends made of unidirectional composites. The quality of the welded joints is assessed by a single-lap shear strength and fracture surface analysis complemented by the microscopic analysis of cross-sections and comparison to a co-consolidated reference. The results showed that the welding process is highly affected by changing welding speeds for a given amplitude. Furthermore, while lower amplitudes lead to significant scatter in the welding quality, higher amplitudes result in increased heating rates and a fully molten energy director even for high welding speeds. Nevertheless, insufficient consolidation at high welding speeds results in porosity in the weld line. Finally, it was observed that thicker, and therefore more compliant, energy directors lead to more uniform melting of the energy director and less deviation in the weld quality for a wider range of welding speeds.

Active Disturbance Rejection Control for Flux Weakening in Interior Permanent Magnet Synchronous Motor Based on Full Speed Range

To address the impact of load disturbances on the full-speed-range control of an interior permanent magnet synchronous motor (PMSM), an active disturbance rejection control (ADRC) method is proposed. The speed loop employs phased field-weakening control (FW) based on ADRC, while the current loop utilizes proportional-integral-derivative (PID) control. Starting from the motor parameters, the Lagrange multiplier method was used to derive the critical speeds for the maximum torque per ampere (MTPA) and maximum torque per voltage (MTPV) ratios, and the timing for the field-weakening control was analyzed. A full-speed-range control model of the motor was established, and an ADRC-based speed loop controller was designed to achieve smooth transitions between high speeds and anti-disturbance solid capabilities. Based on the proposed control strategy, a 21 kW PMSM was used as the research object, and a full-speed-range control simulation model was developed in MATLAB/SIMULINK to verify the strategy. Compared to the traditional PID control, the simulation results demonstrate that the proposed strategy effectively observes and compensates for load disturbances, significantly reducing initial torque oscillations under three different operating conditions. After a sudden load increase, torque oscillations were reduced by 16%, with the stator current reaching steady state 0.03 s faster, response speed improving by 0.02 s, smooth transitions between speed ranges, and enhanced anti-disturbance performance.

Research on extraction and identification of automotive wind noise based on LSTM combined road and drum experiments

Wind noise is a significant source of noise when vehicles are driven at high speeds. While wind tunnel experiments are commonly method to study real automotive wind noise, anechoic wind tunnel laboratory are prohibitive for automakers on account of their high costs and limited experimental period. Therefore, this paper proposes to extract automotive wind noise through combining road experiment and drum experiment, define significant wind noise prime regions, and verify its effectiveness. Subsequently, the Long Short-Term Memory Neural Network algorithm (LSTM) is employed to reveal the complex nonlinear relationship between wind noise and its impact areas, in order to establish an identification model for automotive wind noise. The performance of the model is then compared with Backpropagation Neural Networks (BPNN) and Support Vector Regression (SVR) models. The results indicate that the LSTM wind noise identification model exhibits higher accuracy, shorter training time, and stronger generalization ability, thus demonstrating the superiority of this model.