Local Path Planning Method of the Self-propelled Model Based on Reinforcement Learning in Complex Conditions

Conducting hydrodynamic and physical motion simulation tests using a large-scale self-propelled model under actual wave conditions is an important means for researching environmental adaptability of ships. During the navigation test of the self-propelled model, the complex environment including various port facilities, navigation facilities, and the ships nearby must be considered carefully, because in this dense environment the impact of sea waves and winds on the model is particularly significant. In order to improve the security of the self-propelled model, this paper introduces the Q learning based on reinforcement learning combined with chaotic ideas for the model＇s collision avoidance, in order to improve the reliability of the local path planning. Simulation and sea test results show that this algorithm is a better solution for collision avoidance of the self navigation model under the interference of sea winds and waves with good adaptability.

A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode

Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results.

Study on the coupling calculation method for the launch dynamics of a self-propelled artillery multibody system considering engraving process

The launch dynamics theory for multibody systems emerges as an innovative and efficacious approach for the study of launch dynamics,capable of addressing the challenges of complex modeling,diminished computational efficiency,and imprecise analyses of system dynamic responses found in the dynamics research of intricate multi-rigid-flexible body systems,such as self-propelled artillery.This advancement aims to enhance the firing accuracy and launch safety of self-propelled artillery.Recognizing the shortfall of overlooking the band engraving process in existing theories,this study introduces a novel coupling calculation methodology for the launch dynamics of a self-propelled artillery multibody system.This method leverages the ABAQUS subroutine interface VUAMP to compute the dynamic response of the projectile and barrel during the launch process of large-caliber self-propelled artillery.Additionally,it examines the changes in projectile resistance and band deformation in relation to projectile motion throughout the band engraving process.Comparative analysis of the computational outcomes with experimental data evidences that the proposed method offers a more precise depiction of the launch process of self-propelled artillery,thereby enhancing the accuracy of launch dynamics calculations for self-propelled artillery.

Relationship between self-propelled velocity and Brownian motion for spherical and ellipsoid particles

The Brownian motion of spherical and ellipsoidal self-propelled particles was simulated without considering the effect of inertia and using the Langevin equation and the diffusion coefficient of ellipsoidal particles derived by Perrin.The P´eclet number(Pe)was introduced to measure the relative strengths of self-propelled and Brownian motions.We found that the motion state of spherical and ellipsoid self-propelled particles changed significantly under the influence of Brownian motion.For spherical particles,there were three primary states of motion:1)when Pe<30,the particles were still significantly affected by Brownian motion;2)when Pe>30,the self-propelled velocities of the particles were increasing;and 3)when Pe>100,the particles were completely controlled by the self-propelled velocities and the Brownian motion was suppressed.In the simulation of the ellipsoidal self-propelled particles,we found that the larger the aspect ratio of the particles,the more susceptible they were to the influence of Brownian motion.In addition,the value interval of Pe depended on the aspect ratio.Finally,we found that the directional motion ability of the ellipsoidal self-propelled particles was much weaker than that of the spherical self-propelled particles.

Comparison of Microbubble and Air Layer Injection with Porous Media for Drag Reduction on a Self-propelled Barge Ship Model

Ship resistance issues are related to fuel economy,speed,and cost efficiency.Air lubrication is a promising technique for lowering hull frictional resistance as it is supposed to modify the energy in the turbulent boundary layer and thereby reduce hull friction.In this paper,the objective is to identify the optimum type of air lubrication using microbubble drag reduction(MBDR)and air layer drag reduction(ALDR)techniques to reduce the resistance of a 56-m Indonesian self-propelled barge(SPB).A model with the following dimensions was constructed:length L=2000 mm,breadth B=521.60 mm,and draft T=52.50 mm.The ship model was towed using standard towing tank experimental parameters.The speed was varied over the Froude number range 0.11–0.31.The air layer flow rate was varied at 80,85,and 90 standard liters per minute(SLPM)and the microbubble injection coefficient over the range 0.20–0.60.The results show that the ship model using the air layer had the highest drag reduction up to a maximum of 90%.Based on the characteristics of the SPB,which operates at low speed,the optimum air lubrication type to reduce resistance in this instance is ALDR.

Self-propelled Leidenfrost droplets on femtosecond-laser-induced surface with periodic hydrophobicity gradient

The controllable transfer of droplets on the surface of objects has a wide application prospect in the fields of microfluidic devices,fog collection and so on.The Leidenfrost effect can be utilized to significantly reduce motion resistance.However,the use of 3D structures limits the widespread application of self-propulsion based on Leidenfrost droplets in microelectromechanical system.To manipulate Leidenfrost droplets,it is necessary to create 2D or quasi-2D geometries.In this study,femtosecond laser is applied to fabricate a surface with periodic hydrophobicity gradient(SPHG),enabling directional self-propulsion of Leidenfrost droplets.Flow field analysis within the Leidenfrost droplets reveals that the vapor layer between the droplets and the hot surface can be modulated by the SPHG,resulting in directional propulsion of the inner gas.The viscous force between the gas and liquid then drives the droplet to move.

Passive particles driven by self-propelled particle:The wake effect

This work focuses on numerically studying hydrodynamic interaction between a passive particle and a self-propelled particle,termed a squirmer,by using a two-dimensional lattice Boltzmann method(LBM).It is found that the squirmer can capture a passive particle and propel it simultaneously,provided the passive particle is situated within the squirmer's wake.Our research shows that the critical capture distance,which determines whether the particle is captured,primarily depends on the intensity of the squirmer's dipolarity.The stronger dipolarity of squirmer results in an increased critical capture distance.Conversely,the Reynolds number is found to have minimal influence on this interaction.Interestingly,the passive particle,when driven by the squirmer's wake,contributes to a reduction in the squirmer's drag.This results in a mutual acceleration for both particles.Our findings can provide valuable perspectives for formulating the principles of reducing the drag of micro-swimmers and help to achieve the goal of using micro-swimmers to transport goods without physical tethers.

Nonvanishing optimal noise in cellular automaton model of self-propelled particles

A minimal cellular automaton model is introduced to describe the collective motion of self-propelled particles on two-dimensional square lattice. The model features discretization of directional and positional spaces and single-particle occupation on one lattice site. Contrary to the Vicsek model and its variants, our model exhibits the nonvanishing optimal noise. When the particle density increases, the collective motion is promoted with optimal noise strength and reduced with noise strength out of optimal region. In addition, when the square lattice undergoes edge percolation process, no abrupt change of alignment behaviors is observed at the critical point of percolation.

Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis

Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology

Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.

Application of Self-propelled Boom Sprayers for Control of Rice Insects and Diseases

Comparisons were performed between self-propelled boom sprayer and traditional mechanis, such as knapsack sprayer and sprayer-duster, stretcher-type powered sprayer, as well as single rotor unmanned sprayer and multi-rotor un- manned sprayer. The effects on rice injury, lodging, and rehabilitation were conclud- ed and drug uniform distribution, sedimentation and prevention effects were ana- lyzed. The results showed that the self-propelled boom sprayer is characterized by high degree of automation, convenient operation, high adaptability, and high work efficiency. What＇s more, the sprayed fog quality is better, and fog distribution is more uniform. During the work process, fog loss would be diminished substantially, improving work efficiency and cutting down drug and water. It is notable that the underpart of the sprayer can be widely applied to plant protection in large-scale ar- eas in Jiangsu Province, significantly advancing whole-process mechanization of rice production.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究

建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。

基于24Model的地铁内涝事故原因分析与评估

为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响因素。结果表明:地铁内涝事故一级指标中不安全动作与物态因素最重要,其中影响最大的指标包括擅自更改建筑设计、未按照要求检查水位情况、未及时排水、出入口不符合防汛标准等因素;习惯性不安全行为的权重位居第二,表明该指标因素较为重要,同时安全管理体系得分位居第二,表明该指标因素较易发生。对关键指标采取防范措施,可有效降低风险,从而减少地铁内涝事故的发生。

基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

Classifying wakes produced by self-propelled fish-like swimmers using neural networks

We consider the classification of wake structures produced by self-propelled fish-like swimmers based on local measurements of flow variables.This problem is inspired by the extraordinary capability of animal swimmers in perceiving their hydrodynamic environments under dark condition.We train different neural networks to classify wake structures by using the streamwise velocity component,the crosswise velocity component,the vorticity and the combination of three flow variables,respectively.It is found that the neural networks trained using the two velocity components perform well in identifying the wake types,whereas the neural network trained using the vorticity suffers from a high rate of misclassification.When the neural network is trained using the combination of all three flow variables,a remarkably high accuracy in wake classification can be achieved.The results of this study can be helpful to the design of flow sensory systems in robotic underwater vehicles.

Where is the rudder of a fish?:the mechanism of swimming and control of self-propelled fish school

Numerical simulation and control of self- propelled swimming of two- and three-dimensional biomimetic fish school in a viscous flow are investigated. With a parallel computational fluid dynamics package for the two- and three-dimensional moving boundary problem, which combines the adaptive multi-grid finite volume method and the methods of immersed boundary and volume of fluid, it is found that due to the interactions of vortices in the wakes, without proper control, a fish school swim with a given flap- ping rule can not keep the fixed shape of a queue. In order to understand the secret of fish swimming, a new feedback con- trol strategy of fish motion is proposed for the first time, i,e., the locomotion speed is adjusted by the flapping frequency of the caudal, and the direction of swimming is controlled by the swinging of the head of a fish. Results show that with this feedback control strategy, a fish school can keep the good order of a queue in cruising, turning or swimming around circles. This new control strategy, which separates the speed control and direction control, is important in the construction of biomimetic robot fish, with which it greatly simplifies the control devices of a biomimetic robot fish.

A comparative study of the self-propelled jumping capabilities of coalesced droplets on RTV surfaces and superhydrophobic surfaces

Understanding the mechanism of coalescence-induced self-propelled jumping behavior provides distinct insights in designing and optimizing functional coatings with self-cleaning and anti-icing properties.However,to date self-propelled jumping phenomenon has only been observed and studied on superhydrophobic surfaces,other than those hydrophobic surfaces with weaker but fairish water-repellency,for instance,vulcanized silicon rubber(RTV) coatings.In this work,from the perspective of thermodynamic-based energy balance aspect,the reason that self-propelled jumping phenomenon does not happen on RTV coatings is studied.The apparent contact angles of droplets on RTV coatings can be less than the theoretical critical values therefore cannot promise energy surplus for the coalesced droplets onside.Besides,on RTV and superhydrophobic surfaces,the droplet-size dependent variation characteristics of the energy leftover from the coalescence process are opposite.For the droplets coalescing on RTV coatings,the magnitudes of energy dissipations are more sensitive to the increase in droplet size,compared to that of released surface energy.While for superhydrophobic coatings,the energy generated during the coalescence process can be more sensitive than the dissipations to the change in droplet size.