High Speed Research Articles

A Method for Dynamic Kolsky Bar Compression at High Temperatures: Application to Ti-6Al-4V

Abstract An experimental apparatus for measuring the dynamic behavior of materials subjected to strain rates on the order of 10 $$^3$$ 3 s $$^{-1}$$ - 1 and temperatures up to 800°C with a unique triple actuation system is developed in this work. This system is based on the traditional Kolsky (or split-Hopkinson pressure) bar design, with the addition of an external furnace used to heat the specimen to the desired temperature. A synchronized triple pneumatic actuation system is used to control the motion and timing of the the sample, incident, and transmitted bars. The cold contact time (CCT), or the time during which the heated sample is in contact with the room temperature bars before compression, is measured experimentally and carefully controlled to minimize the development of a temperature gradient across the sample and avoid heating of the bars. Experiments are performed in conjunction with ultra high speed imaging and 2D digital image correlation (DIC), as well as high speed thermal imaging. To verify the viability of the proposed system, experiments were conducted on Ti-6Al-4V (wt.%) at temperatures from 25°C up to and 800°C at an average strain rate of approximately 1200 s $$^{-1}$$ - 1 .

Experimental investigations on ultrasonic elliptical vibration turning of SiCp/Al composites

ABSTRACT This study identifies key factors affecting SiCp/Al surface formation in ultrasonic elliptical vibration assisted turning (UEVT) and conventional turning (CT) by scratch tests, end face cutting experiments and theoretical analysis. It also evaluates cutting parameters’ effects on deformation of SiCp/Al. Experimental findings underscore theimportance of vibration effect and removal rate. At lower cutting speeds, the ironing effect results in a dense morphology during UEVT that is advantageous for enhancing both surface quality and microhardness. The high removal speed increases the particle-tool interaction, promotes the generation and propagation of cracks indeformation zone. Specifically, at a reasonable cutting speed (200 mm/min), the utilization of vibration results in a 59% reduction in surface roughness and a commendable enhancement in microhardness, coupled with a significant suppression of tool wear. The results of this study are expected to provide positive theoretical recommendations for improving the machinability of SiCp/Al in UEVT.

Movement Characteristics of Droplet Deposition in Flat Spray Nozzle for Agricultural UAVs

At present, research on aerial spraying operations with UAVs mainly focuses on the deposition outcomes of droplets, with insufficient depth in the exploration of the movement process of droplet deposition. The movement characteristics of droplet deposition as the most fundamental factors affecting the effectiveness of pesticide application by UAVs are of great significance for improving droplet deposition. This study takes flat spray nozzles as the research object, uses the Particle Image Velocimetry (PIV) technique to obtain movement data of water droplet deposition under the influence of rotor flow fields, and investigates the variation characteristics of droplet deposition speed under different influencing factors. The results show that the deposition speed and the distribution area of high-speed (>12 m/s) particles increase with the increase of rotor speed, spraying pressure, and nozzle size. When the rotor speed increases from 0 r/min to 1800 r/min, the average increase in maximum droplet deposition speed for nozzle models LU120-02, LU120-03 and LU120-04 is 33.26%, 19.02%, and 7.62%, respectively. The rotor flow field significantly increases the number of high-speed droplets, making the dispersed droplet velocity distribution more concentrated. When the rotor speed is 0, 1000, 1500, and 1800 r/min, the average decay rates of droplet deposition speed are 36.72%, 20.00%, 15.47%, and 13.21%, respectively, indicating that the rotor flow field helps to reduce the decrease in droplet deposition speed, enabling droplets to deposit on the target area at a higher speed, reducing drift risk and evaporation loss. This study’s results are beneficial for revealing the mechanism of droplet deposition movement in aerial spraying by plant protection UAVs, improving the understanding of droplet movement, and providing data support and guidance for precise spraying operations.

LG-YOLOv8: A Lightweight Safety Helmet Detection Algorithm Combined with Feature Enhancement

In the realm of construction site monitoring, ensuring the proper use of safety helmets is crucial. Addressing the issues of high parameter values and sluggish detection speed in current safety helmet detection algorithms, a feature-enhanced lightweight algorithm, LG-YOLOv8, was introduced. Firstly, we introduce C2f-GhostDynamicConv as a powerful tool. This module enhances feature extraction to represent safety helmet wearing features, aiming to improve the efficiency of computing resource utilization. Secondly, the Bi-directional Feature Pyramid (BiFPN) was employed to further enrich the feature information, integrating feature maps from various levels to achieve more comprehensive semantic information. Finally, to enhance the training speed of the model and achieve a more lightweight outcome, we introduce a novel lightweight asymmetric detection head (LADH-Head) to optimize the original YOLOv8-n’s detection head. Evaluations on the SWHD dataset confirm the effectiveness of the LG-YOLOv8 algorithm. Compared to the original YOLOv8-n algorithm, our approach achieves a mean Average Precision (mAP) of 94.1%, a 59.8% reduction in parameters, a 54.3% decrease in FLOPs, a 44.2% increase in FPS, and a 2.7 MB compression of the model size. Therefore, LG-YOLOv8 has high accuracy and fast detection speed for safety helmet detection, which realizes real-time accurate detection of safety helmets and an ideal lightweight effect.

High speed innovations in photoacoustic microscopy

High speed innovations in photoacoustic microscopy

Fast and light-efficient remote focusing for volumetric voltage imaging

Voltage imaging holds great potential for biomedical research by enabling noninvasive recording of the electrical activity of excitable cells such as neurons or cardiomyocytes. Camera-based detection can record from hundreds of cells in parallel, but imaging entire volumes is limited by the need to focus through the sample at high speeds. Remote focusing techniques can remedy this drawback, but have so far been either too slow or light-inefficient. Here, we introduce flipped image remote focusing, a remote focusing method that doubles the light efficiency compared to conventional beamsplitter-based techniques and enables high-speed volumetric voltage imaging at 500 volumes/s. We show the potential of our approach by combining it with light sheet imaging in the zebrafish spinal cord to record from >100 spontaneously active neurons in parallel.

Cave morphology and moonmilk deposits of Ryongmun Cavern, Democratic People’s Republic of Korea: A Study for the Conservation of Natural Heritage

The Ryongmun Cavern, registered on the World Heritage Tentative List, is the largest and most beautiful karst cave on the Korean peninsula. The characteristics of the cave morphology and moonmilk deposits in the Ryongmun Cavern were studied. A cross section of the main direction of the cave shows that the Ryongmun Cavern is made up mainly of four strata and this caused 4 stages of decline in underground waterline in the course of cave formation. The cave is mainly characterized by NW–SE-trending, NWW–SEE-trending and NNE– SSW-trending passages. The horizontal passages usually have large and wide spaces, whereas the inclined ones are relatively small and narrow. The cave minerals in the Ryongmun Cavern are mainly calcite and aragonite. In the cave, stalactites, stalagmites, limestone columns, cave pearls, etc. Are calcite; and, anthodites are aragonite. In the cave, speleothems display a wonderful underground landscape in harmony with the cave bedrock and groundwater (streams, waterfalls and ponds). The main scenes of the underground karst landscape in the cave are stalactites, stalagmites, limestone columns, stone waterfalls anthodites, underground waterfalls, and underground ponds.The deposits that have been formed recently on the surface of speleothems and walls in the cave are mainly moonmilk composed of hydromagnesite (Mg5(CO3)4(OH)2•4H2O) with an average particle size of 0.55 μm and chemical composition of MgO–29.43% and CaO–6.28%. The moonmilk is present in a white, fine powder form, a hand-rubbed smooth, and a moisture content of 42.0%. Also, the pH is 10.09, which is alkaline. In the Ryongmun Cavern, moonmilk was formed at sites with very low supply of karst water and relatively high wind speeds. The unique underground karst features provide sufficient evidence for geoheritage value of the cave and the characteristics of moonmilk provide a significant implication for management and preservation of the cave environment.

Influence of speed and line spacing on aerodynamic forces in high speed train passing in tunnels

As train speeds increase, the aerodynamic effects generated during the passage of high-speed trains in tunnels become more pronounced. This article investigates the influence of line spacing on the aerodynamic forces during the passage of high-speed trains in tunnels at different speeds. The research methodology is based on the three-dimensional transient compressible Reynolds-averaged Navier-Stokes (RANS) equations and the k-ω Shear Stress Transport (SST) turbulence model, using overset grid technology to simulate the train passing process in the tunnel. The results show that the aerodynamic drag, lateral force, and lift experienced by the train increase as the line spacing decreases and as the speed increases. line spacing has the greatest impact on aerodynamic lift, followed by lateral force, with drag having the smallest impact. Compared to line spacing, speed has a much larger effect on aerodynamic forces. The aerodynamic forces experienced by the train during tunnel passage are proportional to the square of the train’s speed and have an exponential relationship with the line spacing during train passage.

Study on resistance performance of hexagonal hull form with variation of angle of attack, deadrise, and stern for flat-sided catamaran vessel

Abstract The flat-sided hull vessel was designed with the purpose of simplifying hull production by eliminating the requirement for fairing, bending, and assembly of curved panel lines. Nevertheless, implementing the flat hull concept may marginally increase the hull resistance. The objective of the study is to investigate the impact of the hexagonal hull concept on resistance characteristics when altering the deadrise angle, angle of attack, and stern angle. Additionally, the resistance performances of the proposed hexagonal hulls were compared to evaluate the influence of the hull design geometry parameter. The contribution of this work is to identify the configuration of the design parameters to achieve an ideal level of resistance in a hexagonal catamaran hull design. The findings indicate that a greater angle of attack could potentially enhance wave generation and increase the resistance. Despite the increase in the wave resistance coefficient caused by the increment in deadrise angle, the overall resistance was reduced due to the significant reduction in wetted surface area resulting from the greater deadrise angle. As a result, the decrease in friction resistance was more pronounced than the increase in wave resistance. At last, the stern angle can cause a substantial oscillation in the curved line, resulting in a large increase in wave generation and overall resistance, particularly at high speeds.

Enabling Fast Photoresponse in Hybrid Perovskite/MoS2 Photodetectors by Separating Local Photocharge Generation and Recombination.

Interfacing CH3NH3PbI3 (MAPbI3) with 2D van der Waals materials in lateral photodetectors can suppress the dark current and driving voltage, while the interlayer charge separation also renders slower charge dynamics. In this work, we show that more than one order of magnitude faster photoresponse time can be achieved in MAPbI3/MoS2 lateral photodetectors by locally separating the photocharge generation and recombination through a parallel channel of single-layer MAPbI3. Photocurrent (Iph) mapping reveals electron diffusion lengths of about 20 μm in single-layer MAPbI3 and 4 μm in the MAPbI3/MoS2 heterostructure. The illumination-power scaling of Iph and time-resolved photoluminescence studies point to the dominant roles of the heterostructure region in photogeneration and single-layer MAPbI3 in charge recombination. Our results shed new light on the material design that can concurrently enhance photoresponsivity, reduce driving voltage, and sustain high operation speed, paving the path for developing high-performance lateral photodetectors based on hybrid perovskites.

Intelligent Fault Diagnosis Method Based on Neural Network Compression for Rolling Bearings

Rolling bearings are often exposed to high speeds and pressures, leading to the symmetry in their rotating structure being disrupted, which can lead to serious failures. Intelligent rolling bearing fault diagnosis is a critical part of ensuring operation of machinery, and it has been facilitated by the growing popularity of convolutional neural networks (CNNs). The outstanding performance of fault diagnosis CNNs results from complex and redundant network structures and parameters, resulting in huge storage and computational requirements, which makes it challenging to implement these models in resource-limited industrial devices. This study aims to address this problem by proposing a comprehensive compression method for CNNs that is applied to intelligent fault diagnosis. It involves several different compression methods, including tensor train decomposition, parameter quantization, and knowledge distillation for deep network compression. This results in a significant decrease in redundancy and speeding up the training of CNN models. Firstly, tensor train decomposition is applied to reduce redundant connections in both convolutional and fully connected layers. The next step is to perform parameter quantization to minimize the bits needed for parameter representation and storage. Finally, knowledge distillation is used to restore accuracy to the compressed model. The effectiveness of the proposed approach is confirmed by an experiment and ablation study with different models on several datasets. The results show that it can significantly reduce redundant information and floating-point operations with little degradation in accuracy. Notably, on the CWRU dataset, with about 60% parameter reduction, there is no degradation in our model’s accuracy. The proposed approach is a new attempt at the intelligent fault diagnosis of rolling bearings in industrial equipment.

Numerical and experimental study on the mechanism of added resistance in stepped moonpool under different waves

To study the additional resistance effect of the moonpool during the navigation of the drilling vessel, this paper explores the variation of the drilling vessel resistance under different waves based on a model test and numerical simulation. The difference between the model test and the numerical simulation results is compared, and the mechanism of the added resistance of the moonpool under different waves is revealed. The results show that the technology of numerical simulation is able to accurately simulate the navigation resistance of the drilling vessel in waves. The numerical simulation results closely correspond to the experiment results, and the error range can be controlled within 10%. In the components of the total resistance of the hull, pressure resistance plays a dominant role when the drilling vessel sails in waves. The pressure resistance accounts for about 60%–70% of the total resistance, while the friction resistance accounts for about 30%–40% of the total resistance. At low speed, the average resistance reduction rate of the dissipative equipment is 4.4%; under the condition of medium speed, it is 7.5%; at high speed, it is 9.6%; and the resistance reduction efficiency of the dissipative equipment increases with the increase in speed. The dissipative equipment partially suppresses the eddy's action stage and prevents eddy shedding from entering and directly hitting the back wall, thereby reducing the moonpool's additional pressure resistance. The research results can provide a reference for energy savings and emission reductions in drilling vessels.

On the evolution of the shock waves systems created by the fan blades

Fan is one of the noise sources in a modern engine. The fan noise is especially noticeable during takeoff at high angular rotation speeds. In such operating modes, supersonic flow around the tips of the fan blades is realized, which leads to the formation of shock waves that propagate upstream until they exit of the engine channel. As a result, a specific noise is emitted into the front hemisphere, consisting of harmonics that are multiples of the fan rotation frequency. The paper analyzes the described effect based on a simple model of the propagation of a shock waves system. By using energy analysis, it is shown that the system of shock waves with equal amplitude decays faster than a system of shock waves with a spread in amplitude.

High-entropy doping for high-voltage LiCoO2 with enhanced electrochemical performances

Lithium cobalt oxide (LiCoO2), as a pioneering layered oxide cathode material for lithium-ion batteries (LIBs), possesses exceptional theoretical specific capacity and cycling stability, positioning it as a leading candidate for commercial LIB applications. Boosting the upper-limit of charge voltage of LiCoO2 is a promising strategy to increase the capacity of batteries, vital for advancing energy storage solutions from portable electronics to electric vehicles. Nevertheless, hybrid redox reactions at high voltages speed up oxygen evolution, electrolyte decomposition, and irreversible phase transitions, ultimately causing rapid capacity fading.To address these challenges, we present a novel approach to enhance the structural stability and electrochemical performances of LiCoO2 cathode via La-Al-Mg-Y high-entropy doping. This strategy significantly improves the high-voltage cycling stability of the cathode material by retaining 72.5 % of its initial capacity after 500 cycles at 5 C under 4.6 V. Furthermore, the structural change caused by the phase transition between the O3 and H1-3 phases is remarkably suppressed. This advancement in LIB cathode technology paves the way for the development of high performance batteries and it is crucial for meeting the growing demand for sustainable energy storage.

Regioselective Synthesis of Cycloalkane-fused Pyrazolo[4,3-e]pyridines through Tandem Reaction of 5-aminopyrazoles, Cyclic Ketones and Electron-rich Olefins.

Pyrazolopyridines are interesting fused heterocyclic pharmacophores that combine pyrazole and pyridine; two privileged nuclei extensively studied and with a wide range of applications. They can be obtained by a broad variety of synthetic methods among which multicomponent reactions have gained importance, especially from 5-aminopyrazoles and dielectrophilic reagents. However, the search for new approaches more in tune with sustainable chemistry and the use of unconventional heating in three-component synthesis are open and highly relevant study fields. A novel, practical and efficient three-component synthesis of cycloalkane-fused pyrazolo[ 4,3-e]pyridines was developed through a tandem reaction of 5-aminopyrazoles, cyclic ketones and electron-rich olefins, using microwave induction in perfluorinated solvent and iodine as catalyst. The microwave-induced three-component approach applied in this work promoted the construction of 10 new pyrazolopyridines with high speed and excellent control of regioselectivity, favoring the linear product with good yields; where the versatility of electron-rich olefins in iodine-catalyzed cascade heterocyclizations, granted the additional benefit of easy isolation and the possibility to reuse the fluorous phase. Although pyrazolopyridines have been synthetically explored because of their structural and biological properties, most of the reported synthetic methods use common or even toxic organic solvents and conventional heating or multi-step processes. In contrast, this study applied a multicomponent methodology in a single step by microwave induction and with the versatility provided in this case by the use of perfluorinated solvent, which allowed easy isolation of the final product and recovery of the fluorous phase.

Silica conversion of polysilazanes by low-temperature plasma jet generated from Ar and water-vapor mixed gas

Perhydropolysilazane (PHPS), which contains no organic catalyst, chemically reacts with H2O in the atmosphere by heating it at 450 °C for more than 1 h to turn it into a SiO2 film. If silica conversion can be achieved at temperatures below 100 °C, which plastics can withstand, it may be applicable to a wide range of applications, such as flexible electronics. Here, we report a technique for forming SiO2 films with leakage current characteristics very close to those of thermally oxidized (THOX) films that works at a very low temperature of 52 °C with high speed. Using a 9-kV, 30-kHz power supply, a low-temperature plasma jet containing a gas mixture of Ar and water vapor irradiated an 8 nm thick PHPS thin film, inducing silica conversion at a maximum substrate temperature of 52 °C. The current density-electric field strength (J-E) characteristics of metal oxide semiconductor capacitors fabricated with this SiO2 film showed characteristics very close to those of THOX films. In addition, the mechanism of silica conversion of PHPS through low-temperature plasma jet irradiation using this gas mixture was clarified in real-time FT-IR measurements.

An Improved Transfer Learning Method for Rotor Unbalance Position Identification from Simulated Data to Experimental Data

In the study of dynamic balancing for flexible rotors operating at high speeds, determining the unbalanced position of the rotor has consistently posed significant challenges. Accurate identification of the unbalanced position enables low-speed dynamic balancing to serve as a viable alternative to high-speed methods, ultimately reducing costs and enhancing operational efficiency. Although deep learning techniques utilizing limited labeled data have shown promising results in identifying unbalanced positions, the challenge of gathering a sufficient amount of labeled data for effectively training diagnostic models remains substantial. To address this issue, we propose a Pre-Adaptive Transfer Learning (PATL) approach that employs sample reconstruction through frequency domain correlation analysis. This technique facilitates cross-domain deep transfer recognition of rotor unbalanced positions by transferring insights from simulated dynamic model data to experimental datasets. Compared to existing methodologies, the proposed approach demonstrates significant improvements in both the accuracy and generalization of unbalanced position identification. The novelty of this research lies in the introduction of pre-adaptive transfer learning, which effectively minimizes the disparity between experimental and simulation data, thereby enhancing the model's recognition capabilities. Experimental results indicate that the proposed method achieves effective balancing outcomes across various operating conditions.

Comparative studies "Effect of educational policy on artificial intelligence in the countries of America, Singapore and Iran

Artificial intelligence under the paradigm of the fourth industrial revolution has become one of the fateful trends of societies in such a way that university education methods, as one of the most important social constructions, have influenced the advancement of technology. Undoubtedly, educational policy has changed the speed, depth and extent of artificial intelligence technology Artificial intelligence is one of the most important emerging technologies, which today has caused huge changes in all areas, including educational policymaking, at a high speed. Among the important applications of artificial intelligence in educational policymaking, we can mention the prioritization of issues based on the real needs and demands of the society and the diagnosis of problems based on the existing conditions, which will lead to the design and formulation of macro-educational policies. The use of methods such as neural networks, natural language processing, and machine learning algorithms makes the process of policy making more intelligent and dynamic, and as a result, the role of policymakers in the application of this technology becomes more efficient. Today, new technologies such as artificial intelligence, sensor networks, blockchain are changing aspects of everyday life. The study of artificial intelligence began in the 1940s and in recent years it has overshadowed the government departments of a large number of countries, of which e-government is one of the examples. One of the topics that is analyzed in the discussion of educational policy is the effect of content on artificial intelligence. In other words, understanding the complexities of decision-making processes as well as the importance of the actors involved in such processes, has undoubtedly influenced artificial intelligence and is influenced by it. This article is designed as a review and library method and it examines the educational policies of Iran, America and Singapore in the field of artificial intelligence with an exploratory view.

New Rankine Vortex Models Developed Based on SMAP Measurements

Abstract The L-band passive microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent α of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed Um, the relationship between α and the radius of maximum wind speed (Rm), and the relationship between Rm and the averaged radius of 17 m s−1 (R17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with Um. The second way is to calculate solely with Rm. The third way is to calculate Um and Rm together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2), and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall. Significance Statement Ocean surface wind fields are important driving factors for numerical models to guide evolution forecasting and risk assessment of tropical cyclones. The purpose of this study is to utilize the SMAP products to modify the traditional Rankine vortex model for tropical cyclone surface wind field estimation. Rankine decay exponent was found between 0.3 and 0.9 and positively dependent upon maximum wind speed and its radius. Based on these characteristics, the proposed new Rankine models could calculate the decay exponent and further the TC surface wind field symmetrically with high accuracy, simply using maximum wind and its radius. This paper shows a practical use of SMAP measurements on TC wind field monitoring, analyzing, and modeling.

Improvements in Wave Age-Based Sea and Swell Separation for Offshore Industry Applications

Abstract For offshore wind turbines, an accurate description of the wave conditions is crucial for their design, construction, installation, maintenance, and operation. Typical sea states in the open ocean are often a combination of wind-sea and swell systems which cannot be fully described by a single set of parameters. In such cases the wave conditions are better defined by separating and quantifying the individual wave systems. In this paper, the wave age method has been revisited, and a modification has been proposed to add more functionality to better describe the wind/wave alignment of the wind-sea. A qualitative analysis was performed using offshore spectral energy data from a global wave model. The analysis was carried out for four different geographical locations: the Philippine Sea, the North Sea, the Atlantic Ocean, and the Pacific Ocean. The analysis compares the wind-sea and swell partitions separated by the standard and modified wave age methods. It shows an improved description of the wind-sea compared to the standard equation, especially in the case of high wind speed events and where the wind-sea partition is expected to dominate most of the spectral energy.