Research on simulation of gun muzzle flow field empowered by artificial intelligence

Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper.A data-physical fusion driven framework is proposed.First,the known flow field data is used to initialize the model parameters,so that the parameters to be trained are close to the optimal value.Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation laws.Through two examples,it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems,and has stronger generalization and expansion.The proposed model is used to solve a muzzle flow field,and the safety clearance behind the barrel side is divided.It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same,and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold,which is a dangerous area.Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation accuracy.The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.

Effects of counter-current driven by electron cyclotron waves on neoclassical tearing mode suppression

Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is used with this model to obtain the modified Rutherford equation with co-current and counter-current contributions.Consistent with the reported experimental results,numerical simulations have shown that the localized counter external current can only partially suppress NTM when it is far from the resonant magnetic surface.Under some circumstances,the Ohkawa mechanism dominated current drive(OKCD)by electron cyclotron waves can concurrently create both co-current and counter-current.In this instance,the minimal electron cyclotron wave power that suppresses a particular NTM was calculated by the Rutherford equation.The result is marginally less than when taking co-current alone into consideration.As a result,to suppress NTM using OKCD,one only needs to align the co-current with a greater OKCD peak well with the resonant magnetic surface.The effect of its lower counter-current does not need to be considered because the location of the counter-current deviates greatly from the resonant magnetic surface.

Investigation of system parameters towards safer impact based shock-to-detonation transition in a novel laser driven flyer plate prototype

Laser driven flyer plate technology offers improved safety and reliability for detonation of explosives in industrial applications ranging from mining and stone quarrying to the aerospace and defense industries.This study is based on developing a safer laser driven flyer plate prototype comprised of a laser initiator and a flyer plate subsystem that can be used with secondary explosives.System parameters were optimized to initiate the shock-to-detonation transition(SDT)of a secondary explosive based on the impact created by the flyer plate on the explosive surface.Rupture of the flyer was investigated at the mechanically weakened region located on the interface of these subsystems,where the product gases from the deflagration of the explosive provide the required energy.A bilayer energetic material was used,where the first layer consisted of a pyrotechnic component,zirconium potassium perchlorate(ZPP),for sustaining the ignition by the laser beam and the second layer consisted of an insensitive explosive,cyclotetramethylene-tetranitramine(HMX),for deflagration.A plexiglass interface was used to enfold the energetic material.The focal length of the laser beam from the diode was optimized to provide a homogeneous beam profile with maximum power at the surface of the ZPP.Closed bomb experiments were conducted in an internal volume of 10 cm^(3) for evaluation of performance.Dependency of the laser driven flyer plate system output on confinement,explosive density,and laser beam power were analyzed.Measurements using a high-speed camera resulted in a flyer velocity of 670±20 m/s that renders the prototype suitable as a laser detonator in applications,where controlled employment of explosives is critical.

Effect of power supply parameters on discharge characteristics and sterilization efficiency of magnetically driven rotating gliding arc

Plasma sterilization is a new generation of high-tech sterilization method that is fast,safe,and pollution free.It is widely used in medical,food,and environmental protection fields.Home air sterilization is an emerging field of plasma application,which puts higher requirements on the miniaturization,operational stability,and operating cost of plasma device.In this study,a novel magnetically driven rotating gliding arc(MDRGA)discharge device was used to sterilize Lactobacillus fermentation.Compared with the traditional gas-driven gliding arc,this device has a simple structure and a more stable gliding arc.Simulation using COMSOL Multiphysics showed that adding permanent magnets can form a stable magnetic field,which is conducive to the formation of gliding arcs.Experiments on the discharge performance,ozone concentration,and sterilization effect were conducted using different power supply parameters.The results revealed that the MDRGA process can be divided into three stages:starting,gliding,and extinguishing.Appropriate voltage was the key factor for stable arc gliding,and both high and low voltages were not conducive to stable arc gliding and ozone production.In this experimental setup,the sterilization effect was the best at 6.6 kV.A high modulation duty ratio was beneficial for achieving stable arc gliding.However,when the duty ratio exceeded a certain value,the improvement in the sterilization effect was slow.Therefore,considering the sterilization effect and energy factors comprehensively,we chose 80%as the optimal modulation duty ratio for this experimental device.

Data-model coupling driven stress field measurements

This paper presents a method for measuring stress fields within the framework of coupled data models,aimed at determining stress fields in isotropic material structures exhibiting localized deterioration behavior without relying on constitutive equations in the deteriorated region.This approach contributes to advancing the field of intrinsic equation-free mechanics.The methodology combines measured strain fields with data-model coupling driven algorithms.The gradient and Canny operators are utilized to process the strain field data,enabling the determination of the deterioration region's location.Meanwhile,an adaptive model building method is proposed for constructing coupling driven models.To address the issue of unknown datasets during computation,a dataset updating strategy based on a differential evolutionary algorithm is introduced.The resulting optimal dataset is then used to generate stress field results.Validation against finite element method calculations demonstrates the accuracy of the proposed method in obtaining full-field stresses in specimens with local degradation behavior.

Comparison of the effect of different external electrodes on discharge plasma-assisted diffusion flame stabilization

To optimize the design of plasma injectors,the influence of different external electrodes on plasma-assisted flame stabilization was assessed by using a nonequilibrium plasma injector flame control setup.The electrical characteristics of the injector,flame structure parameters,flame intensity,discharge power,and cost-to-effectiveness ratio under different external electrodes(four mesh electrodes and one copper foil electrode)were analyzed using electrical and optical methods.The results show that reducing the mesh size of the external electrode leads to a decrease in breakdown voltage.Compared with a ceramic dielectric barrier-based injector,an injector with a quartz dielectric barrier produces a higher breakdown voltage under the same conditions.For the same actuation voltage,the discharge current increases as the mesh size of the external electrode decreases,and combustion is enhanced by the discharge plasma;therefore,it is better to adopt a smaller mesh hole size to realize good flame stabilization under a lower actuation voltage.However,under the studied working conditions,reducing the mesh hole size of the external electrode increases the cost-to-effectiveness ratio of plasma injector-based flame stabilization.Thus,considering the cost-to-effectiveness ratio and the weight of the injector,an external electrode with a larger mesh hole size should be chosen,which contradicts the above rule.

Research on the Microstructure Construction Technology of Fully Degraded Polymer Vascular Stent Based on Electric Field Driven 3D Printing

The so-called fourth-generation biodegradable vascular stent has become a research hotspot in thefield of bioengineering because of its good degradation ability and drug-loading characteristics.However,the preparationof polymer-degraded vascular stents is affected by known problem such as poor processflexibility,low formingaccuracy,large diameter wall thickness,limited complex pore structure,weak mechanical properties of radial support and high process cost.In this study,a deposition technique based on a high-voltage electric-field-driven continuous rotating jet is proposed to fabricate fully degraded polymer vascular stents.The experimental results showthat,due to the rotation of the deposition axis,the deposition direction of PCL(polycaprolactone)micro-jet isalways tangent to the surface of the deposition axis.The direction of the viscous drag force is also consistent withthe deposition direction of the jet.It is shown that by setting different rotation speeds of deposition axisωandlinear motion speeds of the nozzle V,the direction of rotation,pitch and angle of the individual printed spiralcurve can be precisely tuned.In the process of multiple spiral curves matching the deposition forming thin walltube mesh,the mesh shape and size of the thin wall tube can be accurately controlled by changing the number ofmatching spiral curves and the size of the matching position bias distance.Finally,the characteristics of a PCLtubular stent sample(with uniform-size microfibers and mesh shape),fabricated under the appropriate processparameters are described in detail.

Data Driven Vibration Control:A Review

With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic communities.Input shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC methods.It convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration separately.Based on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of DDVC.By doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.

A Data-Oriented Method to Optimize Hydraulic Fracturing Parameters of Tight Sandstone Reservoirs

Based on the actual data collected from the tight sandstone development zone, correlation analysis using theSpearman method was conducted to determine the main factors influencing the gas production rate of tightsandstone fracturing. An integrated model combining geological engineering and numerical simulation of fracturepropagation and production was completed. Based on data analysis, the hydraulic fracture parameters wereoptimized to develop a differentiated fracturing treatment adjustment plan. The results indicate that the influenceof geological and engineering factors in the X1 and X2 development zones in the study area differs significantly.Therefore, it is challenging to adopt a uniform development strategy to achieve rapid production increase. Thedata analysis reveals that the variation in gas production rate is primarily affected by the reservoir thickness andpermeability parameters as geological factors. On the other hand, the amount of treatment fluid and proppantaddition significantly impact the gas production rate as engineering factors. Among these factors, the influence ofgeological factors is more pronounced in block X1. Therefore, the main focus should be on further optimizing thefracturing interval and adjusting the geological development well location. Given the existing well location, thereis limited potential for further optimizing fracture parameters to increase production. For block X2, the fracturingparameters should be optimized. Data screening was conducted to identify outliers in the entire dataset, and adata-driven fracturing parameter optimization method was employed to determine the basic adjustment directionfor reservoir stimulation in the target block. This approach provides insights into the influence of geological,stimulation, and completion parameters on gas production rate. Consequently, the subsequent fracturing parameteroptimization design can significantly reduce the modeling and simulation workload and guide field operations toimprove and optimize hydraulic fracturing efficiency.

Optimization of the Gas Generator in Composite Power System with Tip-Jet Rotor

The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.

基于MDA的设计模式建模与模型转换

MDA(model driven architecture)的一个重要意图是将模型作为软件开发的基本单元,以进一步提高软件开发的抽象层次.为此,MDA划分了3种抽象级的模型,并通过建立高抽象级的模型和向低抽象级模型及代码的转换来构造可运行的应用程序.在MDA的框架下,将设计模式作为一种独立的建模和转换单元能够在较高的抽象层次上充分支持复用并提高建模粒度,从而进一步发挥设计模式的优点,提高软件开发效率、降低生产成本.然而,要在MDA的框架下将设计模式作为完整的开发单元来使用,必须解决以模式为单元的建模及转换两个具体问题.针对单元化模式建模的问题,通过扩展MOF(meta object facility)的方式定义了模式单元元模型,并提供了基于此元模型的单元化建模支撑机制,以分离业务模型与模式模型的方式解决了该问题.针对单元化模式模型转换问题,在模式单元元模型的基础上定义了向EJB平台的转换规则.该转换规则使用QVT标准描述,支持单元化的模式模型转换,并具有良好的复用性.

元建模技术研究进展

随着UML(unified modeling language)与MDA(model driven architecture)的兴起和流行,模型已经成为软件开发的核心制品,而模型重要性的提升使得建模语言以及定义建模语言的元模型逐渐成为软件开发中的一个核心要素.软件开发往往涉及多个领域,而不同的领域往往需要不同的建模语言及其建模工具.但是,手工地为不同的建模语言开发建模工具代价高昂.元建模技术是解决这个问题的方法之一,通过元建模,可以根据领域需要定制合适的元模型以定义领域建模语言,进而自动生成支持该建模语言的建模工具.大量的工程实践表明,与领域建模以及MDA相结合,元建模可以大幅度地提高软件开发效率,基于元建模的MDA比基于通用建模语言的MDA更具潜力.在最近的几年中,元建模及其相关技术发展迅猛,不但在技术上取得了长足的进步,而且在产业界也开始出现大规模的商业应用.总结了元建模的现有研究成果,分析和比较了现有元建模工具,探讨了元建模的可能发展方向.对元建模中存在的问题进行分析,并指出了可能的解决途径.

一种模型转换的编织框架

模型转换是MDA(modeldrivenarchitecture)的核心技术之一,也是目前MDA研究的热点.目前,MDA范畴内存在多种模型转换方法和工具,它们之间的异构性造成了模型转换代码重用的困难,并使学习和使用模型转换方法的成本增加.受到模型编织技术的启发,提出了一种基于QVT(modelquery/view/transformation)规范的模型转换编织框架QMTW(QVT-basedmodeltransformationweavingframework)来解决以上缺点.展示了模型转换编织的概念、语义、元模型和语法,以及到目标语言的转换定义,并以一个具体实例说明了本框架的使用方法和优点.QMTW提高了模型转换的抽象层次,统一了多种模型转换语言,并支持OMG最新的模型转换规范,在一定程度上消除了模型转换技术的异构性,同时具有简单、规范、扩展性强3个优点.

一种面向图形化建模语言表示法的元模型

对于图形化的建模语言,为定义其表示法一般需要解决3个问题:如何定义每个建模元素的图形符号,如何定义图形符号之间的位置关系以及如何将表示法映射到抽象语法.为了方便进行模型转换和代码生成,还需要使用模型化的方式描述建模语言的表示法.通过对UML及其语言家族中的表示法进行总结、分析和归纳,提出了一种表示法定义元模型(notation definition metamodel,简称NDM).针对定义表示法所面临的3个问题,NDM被分成基本图元及其布局、基本位置关系和抽象语法桥三部分.使用NDM定义好的表示法模型还可以通过代码生成技术生成可使用的源代码.将NDM与其他几种定义表示法的方法进行了比较,结果表明,NDM与其他方法相比具有优势.NDM已经在元建模工具PKU MetaModeler中实现.介绍了NDM在实际应用中的几个案例.

基于MDA的TRISO-Model模型管理方法及应用

TRISO-Model(tridimensional integrated software development model)是为处理软件开发的复杂性和动态性而提出的三维集成软件开发方法学,其中,多维模型之间的语义一致性维护以及对模型应用中公共操作部分的重用,提出了基于一致语义进行模型管理的需求.给出了基于MDA(model driven architecture)进行模型管理的方法MDA-MMMethod(MDA based model management method),应用MDA的4层模型管理结构,基于MDA核心标准MOF(meta object facility)所提供的公共语义基础管理模型和元模型,MDA-MMMethod支持各种MDA模型操作标准实现在TRSIO-model应用中的重用.开发了相应的支持系统MDA-MMSystem(MDA based model management system),应用于SoftPM的项目实践中.与传统方法相比,模型应用的开发效率得到了显著提高,同时降低了开发成本.最后,给出了模型融合的应用实例介绍.

Material driven workability simulation by FEM including 3D processing maps for magnesium alloy

The three-dimensional （3D） processing maps considering strain based on the two-dimensional （2D） processing maps proposed by PRASAD can describe the distribution of the efficiency of power dissipation and flow instability regions at various temperatures, strain rates and strains, which exhibit intrinsic workability related to material itself. Finite element （FE） simulation can obtain the distribution of strain, strain rate, temperature and die filling status, which indicates state-of-stress （SOS） workability decided by die shape and different processing conditions. On the basis of this, a new material driven analysis method for hot deformation was put forward by the combination of FE simulation with 3D processing maps, which can demonstrate material workability of the entire hot deformation process including SOS workability and intrinsic workability. The hot forging process for hard-to-work metal magnesium alloy was studied, and the 3D thermomechanical FE simulation including 3D processing maps of complex hot forging spur bevel gear was first conducted. The hot forging experiments were carried out. The results show that the new method is reasonable and suitable to determine the aoorooriate nrocess narameters.

Resource allocation based on fairness and QoS provisioning for OFDMA-WLAN system

To satisfy different service requirements of multiple users in the orthogo nal frequency division multiple access wireless local area network OFDMA-WLAN system downlink transmission a resource allocation algorithm based on fairness and quality of service QoS provisioning is proposed. Different QoS requirements are converted into different rate requirements to calculate the QoSs atisfaction level.The optimization object is revised as a fairness-driven resource optimization function to provide fairness. The complex resource allocation problem is divided into channel allocation and power assignment sub-problems. The sub-problems are solved by the bipartite graph matching and water-filling based method.Compared with other algorithms the proposed algorithm sacrifices less data rate for higher fairnes and QoS satisfaction.The sim ulation results show that the proposed algorithm is capableo fp rovi ding QoS and fairness and performs better in a tradeoff among QoS fairness and data rate.

ARCHITECTURE OF DYNAMIC DATA DRIVEN SIMULATION FOR WILDFIRE AND ITS REALIZATION

Dynamic data driven simulation （DDDS） is proposed to improve the model by incorporaing real data from the practical systems into the model. Instead of giving a static input, multiple possible sets of inputs are fed into the model. And the computational errors are corrected using statistical approaches. It involves a variety of aspects, including the uncertainty modeling, the measurement evaluation, the system model and the measurement model coupling ,the computation complexity, and the performance issue. Authors intend to set up the architecture of DDDS for wildfire spread model, DEVS-FIRE, based on the discrete event speeification （DEVS） formalism. The experimental results show that the framework can track the dynamically changing fire front based on fire sen- sor data, thus, it provides more aecurate predictions.