Pulses in ground motions identified through surface partial matching and their impact on seismic rocking consequence

In seismology and earthquake engineering,it is fundamental to identify and characterize the pulse-like features in pulse-type ground motions.To capture the pulses that dominate structural responses,this study establishes congruence and shift relationships between response spectrum surfaces.A similarity search between spectrum surfaces,supplemented with a similarity search in time series,has been applied to characterize the pulse-like features in pulse-type ground motions.The identified pulses are tested in predicting the rocking consequences of slender rectangular blocks under the original ground motions.Generally,the prediction is promising for the majority of the ground motions where the dominant pulse is correctly identified.

Monitoring absolute vertical land motions and absolute sea-level changes from GPS and tide gauges data over French Polynesia

In this study,we estimate the absolute vertical land motions at three tidal stations with collocated Global Navigation Satellite System(GNSS)receivers over French Polynesia during the period 2007-2020,and obtain,as ancillary results,estimates of the absolute changes in sea level at the same locations.To verify our processing approach to determining vertical motion,we first modeled vertical motion at the International GNSS Service(IGS)THTI station located in the capital island of Tahiti and compared our estimate with previous independent determinations,with a good agreement.We obtained the following estimates for the vertical land motions at the tide gauges:Tubuai island,Austral Archipelago-0.92±0.17 mm/yr,Vairao village,Tahiti Iti:-0.49±0.39 mm/yr,Rikitea,Gambier Archipelago-0.43±0.17 mm/yr.The absolute variations of the sea level are:Tubuai island,Austral Archipelago 5.25±0.60 mm/yr,Vairao village,Tahiti Iti:3.62±0.52 mm/yr,Rikitea,Gambier Archipelago 1.52±0.23 mm/yr.We discuss these absolute values in light of the values obtained from altimetric measurements and other means in French Polynesia.

Simulation of multi-support depth-varying earthquake ground motions within heterogeneous onshore and offshore sites

This paper presents a novel approach to model and simulate the multi-support depth-varying seismic motions（MDSMs） within heterogeneous offshore and onshore sites.Based on 1 D wave propagation theory,the three-dimensional ground motion transfer functions on the surface or within an offshore or onshore site are derived by considering the effects of seawater and porous soils on the propagation of seismic P waves.Moreover,the depth-varying and spatial variation properties of seismic ground motions are considered in the ground motion simulation.Using the obtained transfer functions at any locations within a site,the offshore or onshore depth-varying seismic motions are stochastically simulated based on the spectral representation method（SRM）.The traditional approaches for simulating spatially varying ground motions are improved and extended to generate MDSMs within multiple offshore and onshore sites.The simulation results show that the PSD functions and coherency losses of the generated MDSMs are compatible with respective target values,which fully validates the effectiveness of the proposed simulation method.The synthesized MDSMs can provide strong support for the precise seismic response prediction and performance-based design of both offshore and onshore large-span engineering structures.

Maxsurf Motions模块在船舶耐波性上的应用与验证

船舶作为海洋中最主要的运动物体,其在海浪中的运动问题,是船舶适航性、耐波性的基础,同时也是船舶设计建造中的关键步骤。采用Maxsurf Motions模块对4种国际标准船模进行了耐波性计算,验证了Maxsurf Motions中的切片理论和面元法的计算精度与可靠性,探讨了Motions程序在船舶耐波性分析中的可行性,分析了Motions模块计算误差的原因。结果表明:Motions模块对船舶运动响应以及波浪增阻的计算精度基本令人满意。对于附加质量系数和阻尼系数,Motions在中高频波段的计算精度较高。研究成果对Maxsurf Motions的应用起到一定的借鉴和指导作用,同时也提供了一系列耐波性计算的验证算例。

基于Leap Motion手势识别的三维交互系统

随着虚拟交互技术的发展,人们迈入了“体验式经济时代”,消费者越来越关注个性体验,因此,基于Leap Motion手势识别设备,设计了一种三维虚拟室内交互系统。该系统以Unity3D作为开发工具,Leap Motion作为硬件平台,结合C#语言进行脚本的编译,利用3ds Max平台对室内进行场景搭建,通过Unity3D工具将组件整合,设计了七种手势,使用Leap Motion硬件设备对场景中物体进行各种不同的操作。经试验表明,该系统实现了用户与场景中物体的交互能力,可以应用在室内装修和设计等方面,增强人们的体验感与趣味性。

Numerical Study on Aerodynamic Performance of Floating Dual-Rotor Wind Turbines in Heave and Surge Motions

Compared with the traditional wind turbine of a single rotor,dual-rotor wind turbines(DRWTs)have higher wind energy capture efficiency and a more complex structure.Therefore,the aerodynamic performance of the DRWT installed on the floating platform will be greatly affected by the motion caused by wind and wave loads.In this paper,5 MW and 750 kW single rotor wind turbines(SRWTs)are combined into a 5 MW-5 MW DRWT and a 5 MW-750 kW DRWT,and their power output and wake field characteristics in different motions are studied.The flow field is obtained by solving the Reynolds-averaged Navier–Stokes equation(RANS).The overset grid technique is employed to achieve the large-amplitude multiple-degree-of-freedom motion of the DRWT.The overall performance of the 5 MW single rotor wind turbine is determined by a numerical method.For the DRWTs,numerical results show that the surge motion and heave motion both have a negative effect on the power output of the DRWT.The surge motion is a critical factor that causes the power output of the DRWT to periodically change with motion.The average power output of the DRWT influenced by motion is lower than that of a DRWT with a fixed bottom.The surge motion significantly disturbs the wake of the DRWT due to the mutual interference between the upstream and downstream rotors.Under the influence of heave motion,low-velocity regions downstream of the blade tip are enhanced.This study indicates that attenuating the surge and heave motion of offshore DRWT is very significant for improving its efficiency and should be taken into consideration during the design procedure.

Revealing the Fluttering Motions of Mid-Water Trawl Codend Through Sea Trials:Case Study of Antarctic Krill Trawl Codend

The dynamic coupling between the fluttering motions and hydrodynamic characteristics of codend is essential in understanding the trawl selectivity through fish response and the drag force acting on the whole trawl.This study investigated the effect of towing speed,warp length,warp tension,and catch size on the fluttering motions of Antarctic krill trawl codend during net shooting,towing,and hauling by using sea trial data.The time-periodicity of codend oscillation was analyzed by the Morlet wavelet transform method.Results indicated that the period of codend oscillation was between 50 s and 90 s and showed an increasing trend with the warp tension but a decreased value at the towing stage.The coefficient amplitude of codend oscillation was between 0 and 4 at the net shooting and hauling stages,and between 0.2 and 0.6 at the towing stage.The amplitude of codend oscillation increased with the warp tension,towing speed,and catch size,but decreased with the increase of the warp length.In addition,the period of codend oscillation increased with the towing speed at the net shooting and hauling stages,but decreased at the towing stage.These results from codend fluttering motions can improve the understanding of fish behavior and gear shape that modify the hydrodynamic force on the codend instantaneously.

Effects of the probability of pulse-like ground motions on landslide susceptibility assessment in near-fault areas

Earthquake-induced strong near-fault ground motion is typically accompanied by largevelocity pulse-like component,which causes serious damage to slopes and buildings.Although not all near-fault ground motions contain a pulse-like component,it is important to consider this factor in regional earthquake-induced landslide susceptibility assessment.In the present study,we considered the probability of the observed pulse-like ground motion at each site(PP)in the region of an earthquake as one of the conditioning factors for landslide susceptibility assessment.A subset of the area affected by the 1994Mw6.7 Northridge earthquake in California was examined.To explore and verify the effects of PP on landslide susceptibility assessment,seven models were established,consisting of six identical influencing factors(elevation,slope gradient,aspect,distance to drainage,distance to roads,and geology)and one or two factors characterizing the intensity of the earthquake(distance to fault,peak ground acceleration,peak ground velocity,and PP)in logistic regression analysis.The results showed that the model considering PP performed better in susceptibility assessment,with an area under the receiver operating characteristic curve value of 0.956.Based on the results of relative importance analysis,the contribution of the PP value to earthquakeinduced landslide susceptibility was ranked fourth after the slope gradient,elevation,and lithology.The prediction performance of the model considering the pulse-like effect was better than that reported previously.A logistic regression model that considers the pulse-like effect can be applied in disaster prevention,mitigation,and construction planning in near-fault areas.

Evaluation of underground blast-induced ground motions through nearsurface low-velocity geological layers

Surface ground motion produced by underground blasts is significantly influenced by near-surface geological conditions.However,near-surface low-propagation velocity layers were always ignored in past analyses of ground motions due to their thin thickness.With the rising concern about surface ground motions produced by the ascendant scale and frequentness of underground excavation and mining,close attention is gradually paid to ground blast vibrations.Therefore,systemic experiments were conducted and took seven months in an underground mine to clarify the variation of motion from underground rock to surface ground.The attenuation of surface ground peak particle velocities(PPVs)is compared to that in underground rock,and horizontal amplitudes are compared to vertical amplitudes.Differences between bedrock and surface ground vibrations are analyzed to illustrate the site effect of near-surface lower-propagation velocity layers.One-dimensional site response analysis is employed to quantify the influence of different geological profiles on surface ground vibrations.The experimental data and site response analysis allowed the following conclusions:(1)geological site effects mainly produce decreasing dominant frequency(DF)of surface ground vibrations;(2)the site amplification effect of blast vibration needs to be characterized by peak particle displacement(PPD);(3)shear waves(S-waves)begin to dominate and surface Rayleigh waves(R-waves)develop as blast-induced ground vibrations travel upward through rock and lower-velocity layers to the surface.The comparison of response relative displacement to a critical value is best to assess the potential for cracking on surface structures.

基于Leap motion 的大学物理实验虚拟课堂设计

通过利用手势控制器(Leap Motion)技术,设计并实施一套创新的大学物理虚拟实验课程.通过在Unity3D软件中整合Leap Motion,创建一个大学物理实验测量杨氏模量实验场景,主要是利用C#语言进行开发,通过设计出多个模块,包括主界面设计和基本实验组件来完成物理实验的设计.在Leap Motion官网上下载关于Unity3D的SDK资源包并且导入Unity3D中,用其建立手部模型,实现Leap Motion控制器与Unity3D的手部交互实验系统的设计.人机交互技术的引入不仅可以丰富大学物理实验的教学手段,而且还能提高学生的学科理解和实际操作能力,同时培养其创新思维和科技素养.

Positron Emission Tomography Lung Image Respiratory Motion Correcting with Equivariant Transformer

In addressing the challenge of motion artifacts in Positron Emission Tomography (PET) lung scans, our studyintroduces the Triple Equivariant Motion Transformer (TEMT), an innovative, unsupervised, deep-learningbasedframework for efficient respiratory motion correction in PET imaging. Unlike traditional techniques,which segment PET data into bins throughout a respiratory cycle and often face issues such as inefficiency andoveremphasis on certain artifacts, TEMT employs Convolutional Neural Networks (CNNs) for effective featureextraction and motion decomposition.TEMT’s unique approach involves transforming motion sequences into Liegroup domains to highlight fundamental motion patterns, coupled with employing competitive weighting forprecise target deformation field generation. Our empirical evaluations confirm TEMT’s superior performancein handling diverse PET lung datasets compared to existing image registration networks. Experimental resultsdemonstrate that TEMT achieved Dice indices of 91.40%, 85.41%, 79.78%, and 72.16% on simulated geometricphantom data, lung voxel phantom data, cardiopulmonary voxel phantom data, and clinical data, respectively. Tofacilitate further research and practical application, the TEMT framework, along with its implementation detailsand part of the simulation data, is made publicly accessible at https://github.com/yehaowei/temt.

Safe Motion Planning and Control Framework for Automated Vehicles with Zonotopic TRMPC

Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.

A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.

Quantitative analysis of the morphing wing mechanism of raptors:IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy.Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Motion Planning for Autonomous Driving with Real Traffic Data Validation

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning,which enables safe autonomous driving on public roads.In this paper,a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method.To begin with,a trajectory prediction model is established based on the graph neural network(GNN)that is trained utilizing the INTERACTION dataset.Then,the validated trajectory prediction model is used to predict the future trajectories of surrounding road users,including pedestrians and vehicles.In addition,a GNN prediction model-enabled motion planner is developed based on the model predictive control technique.Furthermore,two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach,i.e.,merging and roundabout scenarios.The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

A progressive framework for rotary motion deblurring

The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.

Generative adversarial networks based motion learning towards robotic calligraphy synthesis

Robot calligraphy visually reflects the motion capability of robotic manipulators.While traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters,this article presents a generative adversarial network(GAN)-based motion learning method for robotic calligraphy synthesis(Gan2CS)that can enhance the efficiency in writing complex calligraphy words and reproducing classic calligraphy works.The key technologies in the proposed approach include:(1)adopting the GAN to learn the motion parameters from the robot writing operation;(2)converting the learnt motion data into the style font and realising the transition from static calligraphy images to dynamic writing demonstration;(3)reproducing high-precision calligraphy works by synthesising the writing motion data hierarchically.In this study,the motion trajectories of sample calligraphy images are firstly extracted and converted into the robot module.The robot performs the writing with motion planning,and the writing motion parameters of calligraphy strokes are learnt with GANs.Then the motion data of basic strokes is synthesised based on the hierarchical process of‘stroke-radicalpart-character’.And the robot re-writes the synthesised characters whose similarity with the original calligraphy characters is evaluated.Regular calligraphy characters have been tested in the experiments for method validation and the results validated that the robot can actualise the robotic calligraphy synthesis of writing motion data with GAN.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

On a Compound Poisson Risk Model Perturbed by Brownian Motion with Variable Premium and Tail Dependence between Claims Amounts and Inter-Claim Time

This paper considers the compound Poisson risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. It is assumed that the insurance company’s portfolio is governed by two classes of policyholders. On the one hand, the first class where the amount of claims is high, and on the other hand, the second class where the amount of claims is low, this difference in claim amounts has significant implications for the insurance company’s pricing and risk management strategies. When policyholders are in the first class, they pay an insurance premium of a constant amount c1 and when they are in the second class, the premium paid is a constant amount c2 such that c1 > c2. The nature of claims (low or high) is measured via random thresholds . The study in this work will focus on the determination of the integro-differential equations satisfied by Gerber-Shiu functions and their Laplace transforms in the risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. .

Adaptive Space Expansion for Fast Motion Planning

The sampling process is very inefficient for sam-pling-based motion planning algorithms that excess random sam-ples are generated in the planning space.In this paper,we pro-pose an adaptive space expansion(ASE)approach which belongs to the informed sampling category to improve the sampling effi-ciency for quickly finding a feasible path.The ASE method enlarges the search space gradually and restrains the sampling process in a sequence of small hyper-ellipsoid ring subsets to avoid exploring the unnecessary space.Specifically,for a con-structed small hyper-ellipsoid ring subset,if the algorithm cannot find a feasible path in it,then the subset is expanded.Thus,the ASE method successively does space exploring and space expan-sion until the final path has been found.Besides,we present a particular construction method of the hyper-ellipsoid ring that uniform random samples can be directly generated in it.At last,we present a feasible motion planner BiASE and an asymptoti-cally optimal motion planner BiASE*using the bidirectional exploring method and the ASE strategy.Simulations demon-strate that the computation speed is much faster than that of the state-of-the-art algorithms.The source codes are available at https://github.com/shshlei/ompl.