Velocity equation for grenades while impacting on dry sand media

This paper deals with the collision of sphere shape grenades with sand media.The central issue of the article is the establishing of an empirical velocity equation of the grenade while impacting on sand that is used to solve motion equations of the mechanical mechanism inside the impact grenade fuze.The paper focuses on impact velocities that are lower than 5 m s^(-1).An experiment was conducted to study the velocity of the grenade while impacting on dry sand.A high-speed camera video was used to capture the grenade positions.The grenade velocity in the impact process was generated from these video data.Some types of fitting curves are used to regress the velocity equation of the grenade while interacting with the sand media and the best-fitting model is chosen.The result shows the regression curve has a high correlation with the experiment data for grenade velocities below 5 m s^(-1).The received regression equation is useful for analyzing the working ability of the inertial mechanism inside the impact grenade or analyzing and choosing the appropriate parameters of each part in the inertial mechanism to meet the required characteristics of the mechanism.

Where Is Phase Velocity in Minkowski Space?

In the special theory of relativity, massive particles can travel at neither the speed of light c nor faster. Meanwhile, since the photon was quantized, many have thought of it as a point particle. How pointed? The idea could be a mathematical device or physical simplification. By contrast, the preceding notion of wave-group duality has two velocities: a group velocity vg and a phase velocity vp. In light vp = vg = c;but it follows from special relativity that, in massive particles, vp > c. The phase velocity is the product of the two best measured variables, and so their product constitutes internal motion that travels, verifiably, faster than light. How does vp then appear in Minkowski space? For light, the spatio-temporal Lorentz invariant metric is s2=c2t2−x2−y2−z2, the same in whatever frame it is viewed. The space is divided into 3 parts: firstly a cone, symmetric about the vertical axis ct > 0 that represents the world line of a stationary particle while the conical surface at s = 0 represents the locus for light rays that travel at the speed of light c. Since no real thing travels faster than the speed of light c, the surface is also a horizon for what can be seen by an observer starting from the origin at time t = 0. Secondly, an inverted cone represents, equivalently, time past. Thirdly, outside the cones, inaccessible space. The phase velocity vp, group velocity vg and speed of light are all equal in free space, vp = vg = c, constant. By contrast, for particles, where causality is due to particle interactions having rest mass mo > 0, we have to employ the Klein-Gordon equation with s2=c2t2−x2−y2−z2+mo2c2. Now special relativity requires a complication: vp.vg = c2 where vg c and therefore vp > c. In the volume outside the cones, causality due to light interactions cannot extend beyond the cones. However, since vp > c and even vp >> c when wavelength λ is long, extreme phase velocities are then limited in their causal effects by the particle uncertainty σ, i.e. to vgt ± σ/ω, where ω is the particle angular frequency. This is the first time the phase range has been described for a massive particle.

ST-LSTM-SA:A New Ocean Sound Velocity Field Prediction Model Based on Deep Learning

The scarcity of in-situ ocean observations poses a challenge for real-time information acquisition in the ocean.Among the crucial hydroacoustic environmental parameters,ocean sound velocity exhibits significant spatial and temporal variability and it is highly relevant to oceanic research.In this study,we propose a new data-driven approach,leveraging deep learning techniques,for the prediction of sound velocity fields(SVFs).Our novel spatiotemporal prediction model,STLSTM-SA,combines Spatiotemporal Long Short-Term Memory(ST-LSTM) with a self-attention mechanism to enable accurate and real-time prediction of SVFs.To circumvent the limited amount of observational data,we employ transfer learning by first training the model using reanalysis datasets,followed by fine-tuning it using in-situ analysis data to obtain the final prediction model.By utilizing the historical 12-month SVFs as input,our model predicts the SVFs for the subsequent three months.We compare the performance of five models:Artificial Neural Networks(ANN),Long ShortTerm Memory(LSTM),Convolutional LSTM(ConvLSTM),ST-LSTM,and our proposed ST-LSTM-SA model in a test experiment spanning 2019 to 2022.Our results demonstrate that the ST-LSTM-SA model significantly improves the prediction accuracy and stability of sound velocity in both temporal and spatial dimensions.The ST-LSTM-SA model not only accurately predicts the ocean sound velocity field(SVF),but also provides valuable insights for spatiotemporal prediction of other oceanic environmental variables.

用Velocity Verlet积分器改进HMC抽样方法

Hamilton Monte Carlo (HMC)方法是一种常用的快速抽样方法.在对哈密顿方程进行抽样时,HMC方法使用Leapfrog积分器,这可能造成方程的位置及动量的迭代值在时间上不同步,其产生的误差会降低抽样效率及抽样结果的稳定性.为此,本文提出了IHMC(Improved HMC)方法,该方法用Velocity Verlet积分器替代Leapfrog积分器,每次迭代时都计算两变量在同一时刻的值.为验证方法的效果,本文进行了两个实验,一个是将该方法应用于非对称随机波动率模型(RASV模型)的参数估计,另一个是将方法应用于方差伽马分布的抽样,结果显示:IHMC方法比HMC方法的效率更高、结果更稳定.

In vivo label-free measurement of blood flow velocity symmetry based on dual line scanning third-harmonic generation microscopy excited at the 1700 nm window

Measurement of bloodflow velocity is key to understanding physiology and pathology in vivo.While most measurements are performed at the middle of the blood vessel,little research has been done on characterizing the instantaneous bloodflow velocity distribution.This is mainly due to the lack of measurement technology with high spatial and temporal resolution.Here,we tackle this problem with our recently developed dual-wavelength line-scan third-harmonic generation(THG)imaging technology.Simultaneous acquisition of dual-wavelength THG line-scanning signals enables measurement of bloodflow velocities at two radially symmetric positions in both venules and arterioles in mouse brain in vivo.Our results clearly show that the instantaneous bloodflow velocity is not symmetric under general conditions.

Flood Velocity Prediction Using Deep Learning Approach

Floods are one of the most serious natural disasters that can cause huge societal and economic losses.Extensive research has been conducted on topics like flood monitoring,prediction,and loss estimation.In these research fields,flood velocity plays a crucial role and is an important factor that influences the reliability of the outcomes.Traditional methods rely on physical models for flood simulation and prediction and could generate accurate results but often take a long time.Deep learning technology has recently shown significant potential in the same field,especially in terms of efficiency,helping to overcome the time-consuming associated with traditional methods.This study explores the potential of deep learning models in predicting flood velocity.More specifically,we use a Multi-Layer Perceptron(MLP)model,a specific type of Artificial Neural Networks(ANNs),to predict the velocity in the test area of the Lundesokna River in Norway with diverse terrain conditions.Geographic data and flood velocity simulated based on the physical hydraulic model are used in the study for the pre-training,optimization,and testing of the MLP model.Our experiment indicates that the MLP model has the potential to predict flood velocity in diverse terrain conditions of the river with acceptable accuracy against simulated velocity results but with a significant decrease in training time and testing time.Meanwhile,we discuss the limitations for the improvement in future work.

A froth velocity measurement method based on improved U-Net++semantic segmentation in flotation process

During flotation,the features of the froth image are highly correlated with the concentrate grade and the corresponding working conditions.The static features such as color and size of the bubbles and the dynamic features such as velocity have obvious differences between different working conditions.The extraction of these features is typically relied on the outcomes of image segmentation at the froth edge,making the segmentation of froth image the basis for studying its visual information.Meanwhile,the absence of scientifically reliable training data with label and the necessity to manually construct dataset and label make the study difficult in the mineral flotation.To solve this problem,this paper constructs a tungsten concentrate froth image dataset,and proposes a data augmentation network based on Conditional Generative Adversarial Nets(cGAN)and a U-Net++-based edge segmentation network.The performance of this algorithm is also evaluated and contrasted with other algorithms in this paper.On the results of semantic segmentation,a phase-correlationbased velocity extraction method is finally suggested.

Natural vibration and critical velocity of translating Timoshenko beam with non-homogeneous boundaries

In most practical engineering applications,the translating belt wraps around two fixed wheels.The boundary conditions of the dynamic model are typically specified as simply supported or fixed boundaries.In this paper,non-homogeneous boundaries are introduced by the support wheels.Utilizing the translating belt as the mechanical prototype,the vibration characteristics of translating Timoshenko beam models with nonhomogeneous boundaries are investigated for the first time.The governing equations of Timoshenko beam are deduced by employing the generalized Hamilton's principle.The effects of parameters such as the radius of wheel and the length of belt on vibration characteristics including the equilibrium deformations,critical velocities,natural frequencies,and modes,are numerically calculated and analyzed.The numerical results indicate that the beam experiences deformation characterized by varying curvatures near the wheels.The radii of the wheels play a pivotal role in determining the change in trend of the relative difference between two beam models.Comparing the results unearths that the relative difference in equilibrium deformations between the two beam models is more pronounced with smaller-sized wheels.When the two wheels are of equal size,the critical velocities of both beam models reach their respective minima.In addition,the relative difference in natural frequencies between the two beam models exhibits nonlinear variation and can easily exceed 50%.Furthermore,as the axial velocities increase,the impact of non-homogeneous boundaries on modal shape of translating beam becomes more significant.Although dealing with non-homogeneous boundaries is challenging,beam models with non-homogeneous boundaries are more sensitive to parameters,and the differences between the two types of beams undergo some interesting variations under the influence of non-homogeneous boundaries.

Inverting the rock mass P-wave velocity field ahead of deep buried tunnel face while borehole drilling

Imaging the wave velocity field surrounding a borehole while drilling is a promising and urgently needed approach for extending the exploration range of the borehole point.This paper develops a drilling process detection(DPD)system consisting of a multifunctional sensor and a pilot geophone installed at the top of the drilling rod,geophones at the tunnel face,a laser rangefinder,and an onsite computer.A weighted adjoint-state first arrival travel time tomography method is used to invert the P-wave velocity field of rock mass while borehole drilling.A field experiment in the ongoing construction of a deep buried tunnel in southwestern China demonstrated the DPD system and the tomography method.Time-frequency analysis of typical borehole drilling detection data shows that the impact drilling source is a pulse-like seismic exploration wavelet.A velocity field of the rock mass in a triangular area defined by the borehole trajectory and geophone receiving line can be obtained.Both the borehole core and optical image validate the inverted P-wave velocity field.A numerical simulation of a checkerboard benchmark model is used to test the tomography method.The rapid convergence of the misfits and consistent agreement between the inverted and observed travel times validate the P-wave velocity imaging.

Origin of tradeoff between movement velocity and attachment duration of kinesin motor on a microtubule

Kinesin-1 motor protein is a homodimer containing two identical motor domains connected by a common long coiledcoil stalk via two flexible neck linkers. The motor can step on a microtubule with a velocity of about 1 μm·s-1and an attachment duration of about 1 s under physiological conditions. The available experimental data indicate a tradeoff between velocity and attachment duration under various experimental conditions, such as variation of the solution temperature,variation of the strain between the two motor domains, and so on. However, the underlying mechanism of the tradeoff is unknown. Here, the mechanism is explained by a theoretical study of the dynamics of the motor under various experimental conditions, reproducing quantitatively the available experimental data and providing additional predictions. How the various experimental conditions lead to different decreasing rates of attachment duration versus velocity is also explained.

Damage Evolution of Ballastless Track Concrete Exposed to Flexural Fatigue Loads:The Application of Ultrasonic Pulse Velocity,Impact-echo and Surface Electrical Resistance Method

In order to clarify the fatigue damage evolution of concrete exposed to flexural fatigue loads,ultrasonic pulse velocity(UPV),impact-echo technology and surface electrical resistance(SR) method were used.Damage variable based on the change of velocity of ultrasonic pulse(Du) and impact elastic wave(Di)were defined according to the classical damage theory.The influences of stress level,loading frequency and concrete strength on damage variable were measured.The experimental results show that Du and Di both present a three-stages trend for concrete exposed to fatigue loads.Since impact elastic wave is more sensitive to the microstructure damage in stage Ⅲ,the critical damage variable,i e,the damage variable before the final fracture of concrete of Di is slightly higher than that of Du.Meanwhile,the evolution of SR of concrete exposed to fatigue loads were analyzed and the relationship between SR and Du,SR and Di of concrete exposed to fatigue loads were established.It is found that the SR of concrete was decreased with the increasing fatigue cycles,indicating that surface electrical resistance method can also be applied to describe the damage of ballastless track concrete exposed to fatigue loads.

Micro-destructive assessment of subgrade compaction quality using ultrasonic pulse velocity

The ultrasonic pulse velocity(UPV)correlates significantly with the density and pore size of subgrade filling materials.This research conducts numerous Proctor and UPV tests to examine how moisture and rock content affect compaction quality.The study measures the changes in UPV across dry density and compaction characteristics.The compacted specimens exhibit distinct microstructures and mechanical properties along the dry and wet sides of the compaction curve,primarily influenced by internal water molecules.The maximum dry density exhibits a positive correlation with the rock content,while the optimal moisture content demonstrates an inverse relationship.As the rock content increases,the relative error of UPV measurement rises.The UPV follows a hump-shaped pattern with the initial moisture content.Three intelligent models are established to forecast dry density.The measure of UPV and PSO-BP-NN model quickly assesses compaction quality.

Automatic velocity picking based on optimal key points tracking algorithm

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

Swimming velocity of spherical squirmers in a square tube at finite fluid inertia

The three-dimensional lattice Boltzmann method(LBM)is used to simulate the motion of a spherical squirmer in a square tube,and the steady motion velocity of a squirmer with different Reynolds numbers(Re,ranging from 0.1 to 2)and swimming types is investigated and analyzed to better understand the swimming characteristics of microorganisms in different environments.First,as the Reynolds number increases,the effect of the inertial forces becomes significant,disrupting the squirmer's ability to maintain its theoretical velocity.Specifically,as the Reynolds number increases,the structure of the flow field around the squirmer changes,affecting its velocity of motion.Notably,the swimming velocity of the squirmer exhibits a quadratic relationship with the type of swimming and the Reynolds number.Second,the narrow tube exerts a significant inhibitory effect on the squirmer motion.In addition,although chirality does not directly affect the swimming velocity of the squirmer,it can indirectly affect the velocity by changing its motion mode.

Threshold friction velocity influenced by soil particle size within the Columbia Plateau, northwestern United States

Wind erosion is a geomorphic process in arid and semi-arid areas and has substantial implications for regional climate and desertification.In the Columbia Plateau of northwestern United States,the emissions from fine particles of loessial soils often contribute to the exceedance of inhalable particulate matter(PM)with an aerodynamic diameter of 10μm or less(PM10)according to the air quality standards.However,little is known about the threshold friction velocity(TFV)for particles of different sizes that comprise these soils.In this study,soil samples of two representative soil types(Warden sandy loam and Ritzville silt loam)collected from the Columbia Plateau were sieved to seven particle size fractions,and an experiment was then conducted to determine the relationship between TFV and particle size fraction.The results revealed that soil particle size significantly affected the initiation of soil movement and TFV;TFV ranged 0.304-0.844 and 0.249-0.739 m/s for different particle size fractions of Ritzville silt loam and Warden sandy loam,respectively.PM10 and total suspended particulates(TSP)emissions from a bed of 63-90μm soil particles were markedly higher for Warden sandy loam than for Ritzville silt loam.Together with the lower TFV of Warden sandy loam,dust emissions from fine particles(<100μm in diameter)of Warden sandy loam thus may be a main contributor to dust in the region's atmosphere,since the PM10 emissions from the soil erosion surfaces and its ensuing suspension within the atmosphere constitute an essential process of soil erosion in the Columbia Plateau.Developing and implementing strategic land management practices on sandy loam soils is therefore necessary to control dust emissions in the Columbia Plateau.

Effects of nutrient limitations on the sinking velocity of Thalassiosira weissflogii

The sinking of diatoms is critic al to the formation of oceanic biological pumps and coastal hypoxic zones.However,little is known about the effects of different nutrient restrictions on diatom sinking.In this study,we measured the sinking velocity(SV) of Thalassiosira weissflogii using a new phytoplankton video observation instrument and analyzed major biochemical components under varying nutrient conditions.Our results showed that the SV of T.weissflogii under different nutrient limitation conditions varied substantially.The highest SV of(1.77±0.02) m/d was obtained under nitrate limitation,signific antly surpassing that under phosphate limitation at(0.98±0.13) m/d.As the nutrient limitation was released,the SV steadily decreased to(0.32±0.03) m/d and(0.15±0.05) m/d,respectively.Notably;under conditions with limited nitrate and phosphate concentrations,the SV values of T.weissflogii significantly positively correlated with the lipid content(P <0.001),with R^(2) values of 0.86 and 0.69,respectively.The change of the phytoplankton SV was primarily related to the intracellular compo sition,which is controlled by nutrient conditions but did not significantly correlate with transparent extracellular polymer and biosilica contents.The results of this study help to understand the regulation of the vertical sinking process of diatoms by nutrient restriction and provide new insights into phytoplankton dynamics and their relationship with the marine nutrient structure.

Acoustic Velocity-Based Inversion of the Physical Properties of Sea Ice in the Central Arctic Region

Studying the Arctic sea ice contributes to a comprehensive understanding of the climate system in polar regions and offers valuable insights into the interplay between polar climate change and the global climate and environment.One of the key research aspects is the investigation of the temperature,salinity,and density parameters of sea ice to obtain essential insights.During the 11th Chinese National Arctic Research Expedition,acoustic velocity was measured on an ice core at a short-term ice station,however,temperature,salinity,and density were not measured.In the present work,we utilized a genetic algorithm to invert these obtained acoustic velocity data to sea ice temperature,salinity,and density parameters on the basis of the relationship between acoustic velocity and the physical properties of Arctic summer sea ice.We validated the effectiveness of this inversion procedure by comparing its findings with those of other researchers.The results indicate that within the normalized depth range of 0.43-0.94,the ranges for temperature,salinity,and density are -0.48--0.29℃,1.63-3.35,and 793.1-904.1 kg m^(-3),respectively.

Assessment of liquefaction potential based on shear wave velocity:Strain energy approach

Liquefaction assessment based on strain energy is significantly superior to conventional stress-based methods.The main purpose of the present study is to investigate the correlation between shear wave velocity and strain energy capacity of silty sands.The dissipated energy until liquefaction occurs was calculated by analyzing the results of three series of comprehensive cyclic direct simple shear and triaxial tests on Ottawa F65,Nevada,and Firoozkuh sands with varying silt content by weight and relative densities.Additionally,the shear wave velocity of each series was obtained using bender element or resonant column tests.Consequently,for the first time,a liquefaction triggering criterion,relating to effective overburden normalized liquefaction capacity energy(WL=s’c)to effective overburden stresscorrected shear wave velocity(eVs1)has been introduced.The accuracy of the proposed criteria was evaluated using in situ data.The results confirm the ability of shear wave velocity as a distinguishing parameter for separating liquefied and non-liquefied soils when it is calculated against liquefaction capacity energy(WL=s’c).However,the proposed WL=s’c-Vs1 curve,similar to previously proposed cyclic resistance ratio(CRR)-Vs1 relationships,should be used conservatively for fields vulnerable to liquefaction-induced lateral spreading.

Structural similarity of lithospheric velocity models of Chinese mainland

Existing lithospheric velocity models exhibit similar structures typically associated with the first-order tectonic features,with dissimilarities due to different data and methods used in model generation.The quantification of model structural similarity can help in interpreting the geophysical properties of Earth's interior and establishing unified models crucial in natural hazard assessment and resource exploration.Here we employ the complex wavelet structural similarity index measure(CW-SSIM)active in computer image processing to analyze the structural similarity of four lithospheric velocity models of Chinese mainland published in the past decade.We take advantage of this method in its multiscale definition and insensitivity to slight geometrical distortion like translation and scaling,which is particularly crucial in the structural similarity analysis of velocity models accounting for uncertainty and resolution.Our results show that the CW-SSIM values vary in different model pairs,horizontal locations,and depths.While variations in the inter-model CW-SSIM are partly owing to different databases in the model generation,the difference of tomography methods may significantly impact the similar structural features of models,such as the low similarities between the full-wave based FWEA18 and other three models in northeastern China.We finally suggest potential solutions for the next generation of tomographic modeling in different areas according to corresponding structural similarities of existing models.

Dynamic propagation velocity of a positive streamer in a 3 m air gap under lightning impulse voltage

Streamers represent an important stage in the initiation of gap discharge. In this work, we used an eight-frame intensified charge-coupled device camera to capture the streamer development process when a lightning impulse voltage of 95%–100% U50% was applied in a 3 m rod–plate gap and the streamer velocity was analyzed. Analysis of the observations shows that streamer velocity can be defined by three stages: rapid velocity decline(stage 1), rapid velocity rise(stage 2)and slow velocity decline(stage 3). The effects of electrode shape, applied voltage and gap breakdown or withstanding on streamer velocity were analyzed. The electrode with a larger radius of curvature will result in a higher initial velocity, and a higher voltage amplitude will cause the streamer to propagate faster at stage 3. Gap withstanding or breakdown has no obvious effect on streamer velocity. In addition, the experimental results are compared with previous results and the statistical characteristics of the primary streamer discharge are discussed.