基于构型优选的5G集群无人机协同导航方法

针对现有基于测距的集群UAV协同导航方法普遍忽略了空间构型对定位定能的影响,难以获得精确的导航定位结果,提出一种基于空间构型优选的5G集群UAV协同导航方法。构建了复杂环境下基于5G信号的UAV相对测距误差模型,基于最小几何精度因子(geometric dilution of precision,GDOP)准则建立了协同导航节点寻优策略,实现了协同导航空间构型的实时优选;设计了基于5G测距网络的协同导航滤波器,对UAV导航信息进行在线估计和实时补偿,提高集群UAV的协同定位精度。仿真结果表明:该方法从机定位精度平均提升了约42.05%,为集群UAV实现在卫星不可用条件下的自主导航提供了一种有效的新方法。

Nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in aerospace community:a comparative analysis

The aerospace community widely uses difficult-to-cut materials,such as titanium alloys,high-temperature alloys,metal/ceramic/polymer matrix composites,hard and brittle materials,and geometrically complex components,such as thin-walled structures,microchannels,and complex surfaces.Mechanical machining is the main material removal process for the vast majority of aerospace components.However,many problems exist,including severe and rapid tool wear,low machining efficiency,and poor surface integrity.Nontraditional energy-assisted mechanical machining is a hybrid process that uses nontraditional energies(vibration,laser,electricity,etc)to improve the machinability of local materials and decrease the burden of mechanical machining.This provides a feasible and promising method to improve the material removal rate and surface quality,reduce process forces,and prolong tool life.However,systematic reviews of this technology are lacking with respect to the current research status and development direction.This paper reviews the recent progress in the nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in the aerospace community.In addition,this paper focuses on the processing principles,material responses under nontraditional energy,resultant forces and temperatures,material removal mechanisms,and applications of these processes,including vibration-,laser-,electric-,magnetic-,chemical-,advanced coolant-,and hybrid nontraditional energy-assisted mechanical machining.Finally,a comprehensive summary of the principles,advantages,and limitations of each hybrid process is provided,and future perspectives on forward design,device development,and sustainability of nontraditional energy-assisted mechanical machining processes are discussed.

From concept to commercialization:A review of tubular solid oxide fuel cell technology

The reduced sealing difficulty of tubular solid oxide fuel cells(SOFCs)makes the stacking of tubular cell groups relatively easy,and the thermal stress constraints during stack operation are smaller,which helps the stack to operate stably for a long time.The special design of tubular SOFC structures can completely solve the problem of high-temperature sealing,especially in the design of multiple single-cell series integrated into one tube,where each cell tube is equivalent to a small electric stack,with unique characteristics of high voltage and low current output,which can significantly reduce the ohmic polarization loss of tubular cells.This paper provides an overview of typical tubular SOFC structural designs both domestically and internationally.Based on the geometric structure of tubular SOFCs,they can be divided into bamboo tubes,bamboo flat tubes,single-section tubes,and single-section flat tube structures.Meanwhile,this article provides an overview of commonly used materials and preparation methods for tubular SOFCs,including commonly used materials and preparation methods for support and functional layers,as well as a comparison of commonly used preparation methods for microtubule SOFCs,It introduced the three most important parts of building a fuel cell stack:manifold,current collector,and ceramic adhesive,and also provided a detailed introduction to the power generation systems of different tubular SOFCs,Finally,the development prospects of tubular SOFCs were discussed.

Engineering of geometrical configurations in dual-atom catalysts for electrocatalytic applications

Geometrical configurations play a crucial role in dual-atom catalysts(DACs)for electrocatalytic applications.Significant progress has been made to design DACs electrocatalysts with various geometri-cal configurations,but in-depth understanding the relationship between geometrical configurations and metal-metal interaction mechanisms for designing targeted DACs is still required.In this review,the recent progress in engineering of geometrical configurations of DACs is systematically summarized.Based on the polarity of geometrical configuration,DACs can be classified into two different types that are homonuclear and heteronuclear DACs.Furthermore,with regard to the geometrical configurations of the active sites,homonuclear DACs are identified into adjacent and bridged configurations,and heteronuclear DACs can be classified into adjacent,bridged,and separated configurations.Subsequently,metal-metal interactions in DACs with different geometrical configurations are introduced.Additionally,the applications of DACs in different electrocatalytic reactions are discussed,including the oxygen reduction reaction(ORR),oxygen evolution reaction(OER),hydrogen evolution reaction(HER),and other catalysis.Finally,the future challenges and perspectives for advancements in DACs are high-lighted.This review aims to provide inspiration for the design of highly effcient DACs towards energy relatedapplications.

Modeling Geometrically Nonlinear FG Plates: A Fast and Accurate Alternative to IGA Method Based on Deep Learning

Isogeometric analysis (IGA) is known to showadvanced features compared to traditional finite element approaches.Using IGA one may accurately obtain the geometrically nonlinear bending behavior of plates with functionalgrading (FG). However, the procedure is usually complex and often is time-consuming. We thus put forward adeep learning method to model the geometrically nonlinear bending behavior of FG plates, bypassing the complexIGA simulation process. A long bidirectional short-term memory (BLSTM) recurrent neural network is trainedusing the load and gradient index as inputs and the displacement responses as outputs. The nonlinear relationshipbetween the outputs and the inputs is constructed usingmachine learning so that the displacements can be directlyestimated by the deep learning network. To provide enough training data, we use S-FSDT Von-Karman IGA andobtain the displacement responses for different loads and gradient indexes. Results show that the recognition erroris low, and demonstrate the feasibility of deep learning technique as a fast and accurate alternative to IGA formodeling the geometrically nonlinear bending behavior of FG plates.

Sliding and damming properties of granular debris with different geometric configurations and grain size distributions

Granular debris plays a significant role in determining damming deposit characteristics. An indepth understanding of how variations in grain size distribution(GSD) and geometric configurations impact the behavior of granular debris during the occurrence of granular debris is essential for precise assessment and effective mitigation of landslide hazards in mountainous terrains. This research aims to investigate the impact of GSD and geometric configurations on sliding and damming properties through laboratory experiments. The geometric configurations were categorized into three categories based on the spatial distribution of maximum volume: located at the front(Type Ⅰ), middle(Type Ⅱ), and rear(Type Ⅲ) of the granular debris. Our experimental findings highlight that the sliding and damming processes primarily depend on the interaction among the geometric configuration, grain size, and GSD in granular debris. Different sliding and damming mechanisms across various geometric configurations induce variability in motion parameters and deposition patterns. For Type Ⅰ configurations, the front debris functions as the critical and primary driving component, with energy dissipation primarily occurring through inter-grain interactions. In contrast, Type Ⅱ configurations feature the middle debris as the dominant driving component, experiencing hindrance from the front debris and propulsion from the rear, leading to complex alterations in sliding motion. Here, energy dissipation arises from a combination of inter-grain and grain-substrate interactions. Lastly, in Type Ⅲ configurations, both the middle and rear debris serve as the main driving components, with the rear sliding debris impeded by the front. In this case, energy dissipation predominantly results from grainsubstrate interaction. Moreover, we have quantitatively demonstrated that the inverse grading in damming deposits, where coarse grain moves upward and fine grain moves downward, is primarily caused by grain sorting due to collisions among the grains and between the grain and the base. The impact of grain on the horizontal channel further aids grain sorting and contributes to inverse grading. The proposed classification of three geometric configurations in our study enhances the understanding of damming properties from the view of mechanism, which provides valuable insights for related study about damming granular debris.

Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

基于实际预压载作业的自升式平台环境载荷图谱绘制新思路

The environmental load chart is an important technical support required for the jack-up drilling platform to facilitate its adaptation to different operating waters and ensure the safety of operation.This chart is a crucial part of the platform operation manual.The chart data are closely related to external factors such as water depth,wind,wave,and current conditions of the working water,as well as to the structural characteristics of the platform itself and the number of variable loads.This study examines the platform state under extreme wind,wave,and current conditions during preloading.In addition,this study focuses on the difference between the ultimate reaction force of the pile leg during preloading and the reaction force of the pile leg without considering any environmental load before preloading.Furthermore,the relationship between the difference and the new reaction force of the pile leg caused by the combination of different environmental conditions is established to facilitate the construction of a new form of environmental load chart.The newly formed chart is flexible and simple;thus,it can be used to evaluate the environmental adaptability of the platform in the target well location and provides the preloading target demand or variable load limit according to the given environmental constraints.Moreover,the platform can perform personalized preloading operations,thereby improving its capability to cope with complex geological conditions,such as reducing punch-through risks.This condition reduces the load on jacking system devices and increases its service life.

Geometric properties of the first singlet S-wave excited state of two-electron atoms near the critical nuclear charge

The geometric structure parameters and radial density distribution of 1s2s1S excited state of the two-electron atomic system near the critical nuclear charge Z_(c)were calculated in detail under tripled Hylleraas basis set.Contrary to the localized behavior observed in the ground and the doubly excited 2p^(23)Pe states,for this state our results identify that while the behavior of the inner electron increasingly resembles that of a hydrogen-like atomic system,the outer electron in the excited state exhibits diffused hydrogen-like character and becomes perpendicular to the inner electron as nuclear charge Z approaches Z_(c).This study provides insights into the electronic structure and stability of the two-electron system in the vicinity of the critical nuclear charge.

Boosting Electrochemical Urea Synthesis via Constructing Ordered Pd–Zn Active Pair

Electrochemical co-reduction of nitrate(NO_(3)^(-))and carbon dioxide(CO_(2))has been widely regarded as a promising route to produce urea under ambient conditions,however the yield rate of urea has remained limited.Here,we report an atomically ordered intermetallic pallium-zinc(PdZn)electrocatalyst comprising a high density of PdZn pairs for boosting urea electrosynthesis.It is found that Pd and Zn are responsible for the adsorption and activation of NO_(3)^(-)and CO_(2),respectively,and thus the co-adsorption and co-activation NO_(3)^(-)and CO_(2) are achieved in ordered PdZn pairs.More importantly,the ordered and well-defined PdZn pairs provide a dual-site geometric structure conducive to the key C-N coupling with a low kinetical barrier,as demonstrated on both operando measurements and theoretical calculations.Consequently,the PdZn electrocatalyst displays excellent performance for the co-reduction to generate urea with a maximum urea Faradaic efficiency of 62.78%and a urea yield rate of 1274.42μg mg^(-1) h^(-1),and the latter is 1.5-fold larger than disordered pairs in PdZn alloys.This work paves new pathways to boost urea electrosynthesis via constructing ordered dual-metal pairs.

Enhancing Ulcerative Colitis Diagnosis:A Multi-Level Classification Approach with Deep Learning

The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis,a condition with significant clinical implications.However,endoscopic assessment is susceptible to inherent variations,both within and between observers,compromising the reliability of individual evaluations.This study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease severity.To initiate this endeavor,a multi-faceted approach is embarked upon.The dataset is meticulously preprocessed,enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization(CLAHE).A diverse array of data augmentation techniques,encompassing various geometric transformations,is leveraged to fortify the dataset’s diversity and facilitate effective feature extraction.A fundamental aspect of the approach involves the strategic incorporation of transfer learning principles,harnessing a modified ResNet-50 architecture.This augmentation,informed by domain expertise,contributed significantly to enhancing the model’s classification performance.The outcome of this research endeavor yielded a highly promising model,demonstrating an accuracy rate of 86.85%,coupled with a recall rate of 82.11%and a precision rate of 89.23%.

几何形状对气垫升力的影响研究

One of the crucial and challenging issues for researchers is presenting an appropriate approach to evaluate the aerodynamic characteristics of air cushion vehicles(ACVs)in terms of system design parameters.One of these issues includes introducing a suitable approach to analyze the effect of geometric shapes on the aerodynamic characteristics of ACVs.The main novelty of this paper lies in presenting an innovative method to study the geometric shape effect on air cushion lift force,which has not been investigated thus far.Moreover,this paper introduces a new approximate mathematical formula for calculating the air cushion lift force in terms of parameters,including the air gap,lateral gaps,air inlet velocity,and scaling factor for the first time.Thus,we calculate the aerodynamic lift force applied to nine different shapes of the air cushions used in the ACVs in the present paper through the ANSYS Fluent software.The geometrical shapes studied in this paper are rectangular,square,equilateral triangle,circular,elliptic shapes,and four other combined shapes,including circle-rectangle,circle-square,hexagonal,and fillet square.Results showed that the cushion with a circular pattern produces the highest lift force among other geometric shapes with the same conditions.The increase in the cushion lift force can be attributed to the fillet with a square shape and its increasing radius compared with the square shape.

Influence of manufacturing process-induced geometrical defects on the energy absorption capacity of polymer lattice structures

Modern additive manufacturing processes enable fabricating architected cellular materials of complex shape,which can be used for different purposes.Among them,lattice structures are increasingly used in applications requiring a compromise among lightness and suited mechanical properties,like improved energy absorption capacity and specific stiffness-to-weight and strength-to-weight ratios.A dedicated modeling strategy to assess the energy absorption capacity of lattice structures under uni-axial compression loading is presented in this work.The numerical model is developed in a non-linear framework accounting for the strain rate effect on the mechanical responses of the lattice structure.Four geometries,i.e.,cubic body centered cell,octet cell,rhombic-dodecahedron and truncated cuboctahedron 2+,are investigated.Specifically,the influence of the relative density of the representative volume element of each geometry,the strain-rate dependency of the bulk material and of the presence of the manufacturing process-induced geometrical imperfections on the energy absorption capacity of the lattice structure is investigated.The main outcome of this study points out the importance of correctly integrating geometrical imperfections into the modeling strategy when shock absorption applications are aimed for.

Quantification of grain boundary effects on the geometrically necessary dislocation density evolution and strain hardening of polycrystalline Mg-4Al using in situ tensile testing in scanning electron microscope and HR-EBSD

In situ tensile testing in a scanning electron microscope(SEM)in conjunction with high-resolution electron backscatter diffraction(HR-EBSD)under load was used to characterize the evolution of geometrically necessary dislocation(GND)densities at individual grain boundaries as a function of applied strain in a polycrystalline Mg-4Al alloy.The increase in GND density was investigated at plastic strains of 0%,0.6%,2.2%,3.3% from the area including 76 grains and correlated with(i)geometric compatibility between slip systems across grain boundaries,and(ii)plastic incompatibility.We develop expressions for the grain boundary GND density evolution as a function of plastic strain and plastic incompatibility,from which uniaxial tensile stress-strain response of polycrystalline Mg-4Al are computed and compared with experimental measurement.The findings in this study contribute to understanding the mechanisms governing the strain hardening response of single-phase polycrystalline alloys and more reliable prediction of mechanical behaviors in diverse microstructures.

Geometric regulation of collective cell tangential ordering migration

Collective cell migration is a coordinated movement of multi-cell systems essential for various processes throughout life.The collective motions often occur under spatial restrictions,hallmarked by the collective rotation of epithelial cells confined in circular substrates.Here,we aim to explore how geometric shapes of confinement regulate this collective cell movement.We develop quantitative methods for cell velocity orientation analysis,and find that boundary cells exhibit stronger tangential ordering migration than inner cells in circular pattern.Furthermore,decreased tangential ordering movement capability of collective cells in triangular and square patterns are observed,due to the disturbance of cell motion at unsmooth corners of these patterns.On the other hand,the collective cell rotation is slightly affected by a convex defect of the circular pattern,while almost hindered with a concave defect,also resulting from different smoothness features of their boundaries.Numerical simulations employing cell Potts model well reproduce and extend experimental observations.Together,our results highlight the importance of boundary smoothness in the regulation of collective cell tangential ordering migration.

Robust Human Interaction Recognition Using Extended Kalman Filter

In the field of computer vision and pattern recognition,knowledge based on images of human activity has gained popularity as a research topic.Activity recognition is the process of determining human behavior based on an image.We implemented an Extended Kalman filter to create an activity recognition system here.The proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the image.To minimize noise,we use Gaussian filters.Extraction of silhouette using the statistical method.We use Binary Robust Invariant Scalable Keypoints(BRISK)and SIFT for feature extraction.The next step is to perform feature discrimination using Gray Wolf.After that,the features are input into the Extended Kalman filter and classified into relevant human activities according to their definitive characteristics.The experimental procedure uses the SUB-Interaction and HMDB51 datasets to a 0.88%and 0.86%recognition rate.

Nonlinear dynamics of a circular curved cantilevered pipe conveying pulsating fluid based on the geometrically exact model

Due to the novel applications of flexible pipes conveying fluid in the field of soft robotics and biomedicine,the investigations on the mechanical responses of the pipes have attracted considerable attention.The fluid-structure interaction(FSI)between the pipe with a curved shape and the time-varying internal fluid flow brings a great challenge to the revelation of the dynamical behaviors of flexible pipes,especially when the pipe is highly flexible and usually undergoes large deformations.In this work,the geometrically exact model(GEM)for a curved cantilevered pipe conveying pulsating fluid is developed based on the extended Hamilton's principle.The stability of the curved pipe with three different subtended angles is examined with the consideration of steady fluid flow.Specific attention is concentrated on the large-deformation resonance of circular pipes conveying pulsating fluid,which is often encountered in practical engineering.By constructing bifurcation diagrams,oscillating shapes,phase portraits,time traces,and Poincarémaps,the dynamic responses of the curved pipe under various system parameters are revealed.The mean flow velocity of the pulsating fluid is chosen to be either subcritical or supercritical.The numerical results show that the curved pipe conveying pulsating fluid can exhibit rich dynamical behaviors,including periodic and quasi-periodic motions.It is also found that the preferred instability type of a cantilevered curved pipe conveying steady fluid is mainly in the flutter of the second mode.For a moderate value of the mass ratio,however,a third-mode flutter may occur,which is quite different from that of a straight pipe system.

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing communities.In Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for communication.However,existing JSL recognition systems have faced significant performance limitations due to inherent complexities.In response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning features.Our system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL gestures.Simultaneously,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second stream.Then,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL gestures.After reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the classification.To assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)dataset.Our results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

Quantum geometric tensor and the topological characterization of the extended Su-Schrieffer-Heeger model

We investigate the quantum metric and topological Euler number in a cyclically modulated Su-Schrieffer-Heeger(SSH)model with long-range hopping terms.By computing the quantum geometry tensor,we derive exact expressions for the quantum metric and Berry curvature of the energy band electrons,and we obtain the phase diagram of the model marked by the first Chern number.Furthermore,we also obtain the topological Euler number of the energy band based on the Gauss-Bonnet theorem on the topological characterization of the closed Bloch states manifold in the first Brillouin zone.However,some regions where the Berry curvature is identically zero in the first Brillouin zone result in the degeneracy of the quantum metric,which leads to ill-defined non-integer topological Euler numbers.Nevertheless,the non-integer"Euler number"provides valuable insights and an upper bound for the absolute values of the Chern numbers.

透空结构与半潜式风机集成系统耦合运动响应特性分析

A novel semi-submersible platform is proposed for 5 MW wind turbines.This concept focuses on an integrated system formed by combining porous shells with a semi-submersible platform.A coupled aerodynamic–hydrodynamic–mooring analysis of the new system is performed.The motion responses of the novel platform system and the traditional platform are compared.The differences in hydrodynamic performance between the two platforms are also evaluated.The influence of the geometric parameters(porosity,diameter,and wall thickness)of porous shells on the motion response behavior of the new system is studied.Overall,the new semi-submersible platform exhibits superior stability in terms of pitch and heave degrees of freedom,demonstrating minimal effects on the motion response in the surge degree of freedom.