Data driven prediction of fragment velocity distribution under explosive loading conditions

This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.

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-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.

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-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.

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.

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.

磁驱动固体套筒实验模拟中的电流系数

采用不可压缩理论模型,对FP-2装置上开展的磁驱动固体套筒实验进行了模拟分析。模拟结果表明,无论是二维磁流体力学理论模型,还是其他不可压缩理论模型,回流罩结构磁驱动固体套筒的边界磁感应强度公式中都包含一个小于1的套筒电流系数。对不同套筒厚度、不同套筒半径条件下磁驱动固体套筒实验的电流系数进行了模拟,发现电流系数不仅与套筒内半径有关,还与套筒厚度有关;套筒内半径越大,套筒电流系数越小;套筒厚度越大,套筒电流系数越小。准确掌握磁驱动固体套筒电流系数的变化规律,可使磁流体程序从磁驱动固体套筒实验的后验模拟发展为精确预测,使磁流体力学模型真正具备正确设计和指导磁驱动固体套筒相关实验的理论能力。

基于简易冲击分解模型的爆轰驱动硅橡胶数值模拟及实验解读

为了反映爆轰驱动下硅橡胶发生冲击分解反应的物理过程,提出了一种简易的硅橡胶冲击分解模型。基于该模型,对爆轰驱动含硅橡胶夹层钢板实验进行了模拟,并分析解读了钢板的自由面速度。结果表明,实验中硅橡胶发生了冲击分解反应,导致钢板的自由面速度曲线出现了首次起跳中间速度平台及首次起跳速度峰值降低的现象。受硅橡胶冲击分解影响,首次入射波压力将在临界冲击分解压力附近弛豫一段时间,再继续升高至最高压力。该压力波作用于钢板的自由面后,出现了自由面速度在中间速度平台停留一段时间,之后继续升高至速度峰值的现象。硅橡胶冲击分解后的气相物质可压缩性较高,首次加载波内较多的能量被用于压缩气体做功,导致首次波传播至自由面时能量衰减,峰值压力降低,首次起跳速度峰值降低。

建筑群立面风驱雨捕集特性

风驱雨作为建筑围护结构中最重要的湿源,对建筑围护结构的热湿性能、力学性能、耐久性、建筑能耗和碳排放等均有重要影响。很多学者对建筑立面风驱雨展开深入的研究,但研究对象多为独栋建筑。实际上,中国建筑多以建筑群落的形式存在,建筑自身对风场有干扰,建筑群内各建筑立面的风向和风速均可能会发生较大变化,从而影响入侵到建筑立面的风驱雨。为了揭示建筑群内各建筑立面的风驱雨捕集特性,基于风相和雨相质量和动量守恒原理,采用欧拉多相流方法建立并验证建筑风驱雨模型,并应用该模型对建筑群立面的风驱雨捕集特性进行分析。以广州地区为例,由结果可知:建筑群立面风驱雨捕集比与独栋建筑立面风驱雨捕集比相比有较大差异,其中最大差异高达26.3%,最小差异亦可达5.2%。另外,由于受风阻效应的影响,建筑群内各建筑立面的捕集比也存在差异。

基于正系统分析的不确定非线性系统性能驱动控制方法

针对一类不确定非线性系统,提出一种保证系统状态满足预设边界性能函数的新型性能驱动控制(Performancedriven control,PDC)方法.不同于传统预设性能控制(Prescribed performance control,PPC)方法中对误差与边界性能函数的比值进行非线性变换的思路,本文基于保证状态量与上下边界的两个误差量均始终非负这一思想,引入基于Metzler矩阵的正系统分析理论,并结合切换控制技术,以最终保证系统状态始终在预设性能函数之内.系统的稳定性取决于边界性能函数的选取,而不改变控制器的形式.给出针对一类不确定非线性系统的控制设计、稳定性分析和方法讨论,数值仿真例子验证了所提出方法的有效性.

项目驱动下机械创新设计课程思专创融合教学模式构建与实践

针对新工科教育下国家对综合性、复杂型工程科技人才的培养需求,基于成果导向教育(OBE)与工程认证教育理念,结合机械创新设计课程特点,河北农业大学机电工程学院积极探索和实践项目驱动式的专创融合教学模式。以专业理论为主线,以立德树人为核心目标,通过科研项目与双创作品项目驱动,将创新创业思维工具融入课程教学,引导学生自主探究学习和创新设计实践,构建了“四线并驱,两赛促学”的思专创融合教学新范式,为专业课程专创融合的实施提供了有益的借鉴和参考。

需求驱动型档案资源数据化开发模式探析

聚焦档案资源数据化发展态势与档案利用需求数据化转型,全面探析需求驱动型档案资源数据化开发模式概念内涵、要素结构及其实现策略。在需求驱动型档案资源数据化开发模式下,档案部门以用户档案利用需求为决策导向,通过技术赋能,推动档案资源由“模拟态”“数字态”向“数据态”转变,满足用户多元多样、精准智能、便捷智慧的档案数据资源利用需求。需求驱动型档案资源数据化开发模式主要由开发主体、开发客体、开发环境与开发策略四大核心因子构成,需要重点从用户档案利用需求调研、档案资源数据化开发产品供给评估与档案资源数据化开发体制机制创新三方面系统优化档案资源数据化开发环境,激活档案资源数据化开发生态活力,变“死”档案为“活”档案、“档案库”为“思想库”,全面提升档案资源数据竞争力、文化软实力与社会影响力,推动国家档案事业高质量发展。

基于电压-功率灵敏度的有源配电网数据驱动电压协调控制策略

随着分布式光伏渗透率的不断提高,实现配电网电压的快速精确调控变得愈加重要。首先,建立多输入-多输出的电压-功率灵敏度BP神经网络回归预测模型,得到功率参数、节点电压与电压-功率灵敏度间的非线性映射关系;其次,构建高比例光伏有源配电网电压协调控制策略,基于电压-功率灵敏度降序调控原则,通过无功补偿和有功削减结合的两阶段电压调控模式实现配电网节点电压的快速调控;最后,利用IEEE 33和IEEE 141节点典型配电系统的仿真,计算分析验证所提方法的正确性和有效性。

数据驱动的个性化学习:实然问题、应然逻辑与实现路径

教育数字化转型的全面推进和人工智能在教育中的广泛应用,为破解个性化学习难题提供了切实可行的途径,数据驱动的个性化学习已成为教育高质量发展的必由之路。然而,当前数据驱动的个性化学习普遍存在着学习行为感知与状态评价精度不高、学习特征挖掘不准、学习规律挖掘不全、学习问题溯源不深、学习干预精度不佳等瓶颈性难题。为此,研究从情境感知、主体理解和智能干预等方面深入剖析了数据驱动个性化学习的应然逻辑。在此基础上,从学习行为数据有效感知与理解、学习效果精准评估的个性化学习追踪、薄弱知识点和异常学习行为的学习问题成因溯源、潜在交互学习规律发现的教育知识图谱高阶推理、公共学习路网构建与高适配个性化学习路径规划等方面,讨论了数据驱动个性化学习的实现路径和方法。

基于递归本征正交分解与强跟踪扩展卡尔曼滤波的结构损伤识别

针对目前已有损伤识别方法难以实时跟踪结构损伤且计算量大的问题,提出了一种基于递归本征正交分解(recursive proper orthogonal decomposition,RPOD)与强跟踪扩展卡尔曼滤波(strong tracking extended Kalman filter,STEKF)相结合的模型降阶与结构损伤在线识别方法,对动载荷作用下的结构损伤识别进行了研究。利用RPOD方法在线更新并实时建立反映结构状态的降阶模型,解决未知载荷作用下多自由度结构动力分析计算量大且难以收敛的问题,同时跟踪损伤的演化并对其进行定位;通过STEKF方法跟踪降阶模型的状态向量,识别因损伤而退化的降阶模型参数。分别采用六层剪切型框架的数值模拟与三层钢框架的模型试验验证了该方法的可行性,结果表明,所提出的方法能够准确建立降阶模型并跟踪降阶模型参数的时变历程,同时可以有效地识别出剪切型建筑结构损伤的位置和程度,即使在处理高程度噪声时仍有较高的精度。

轮毂电动机驱动车辆并联式复合制动策略

基于并联式轮毂电动机驱动实车构型,分析影响制动能量回收效率的主要因素,采用联邦卡尔曼滤波纵向车速估计算法,提出了三层式复合制动控制策略.该策略中的制动决策层根据踏板输入信号和行驶状态来识别制动工况,并进入相应的制动模式.制动控制层根据制动决策层的指令,在常规制动工况下通过粒子群优化(PSO)算法优化前、后轮电制动力矩分配,实现电池有效回收效率最大化;紧急制动工况下,通过模糊自整定PID算法实现车辆在不同附着路面上各轮滑移率的安全有效控制,优化了制动防抱死控制的鲁棒性,提高制动安全性.制动执行层响应制动控制层的指令,设计了电制动补偿机制,以迅速补偿调节各轮轮缸的压力误差,提高车辆制动稳定性.最后实车验证了该复合控制策略的有效性.

自驱动双关节模组同步控制系统研究

针对自驱动关节臂测量机双关节模组的双电机同步控制问题,根据双关节模组的组成结构和工作原理设计了一种双关节模组同步控制系统。该系统采用LabVIEW软件搭建双电机的上位机控制界面,主控制器为FPGA,两者通过USB串口通信;STM32为双关节模组内部的核心处理器,通过CAN总线与主控制器通信。通过设定不同的负载和速度进行了正反转对比实验,得到双关节模组电机最大转速误差为4.26%,关节转角的最大误差为0.25°,两电机同步时间控制精度为2 ms,验证了双关节模组在负载状态下仍满足技术指标要求,为提高传动精度提供了依据。

地方高校计算机专业研究生科研驱动教学模式研究

研究生的科研与创新能力培养是国家创新体系构建的重要保障。然而,对于地方高校计算机专业研究生培养而言,仍存在科研启动难的问题。为此,文章探讨科研驱动式教学模式,通过文献综述和现状分析,构建一个以科研为核心的教学模式。该模式结合产教融合、科教融汇理念,旨在提升地方高校计算机专业研究生的科研兴趣和能力。分析结果表明,此模式能有效解决教学与科研脱节的问题,提高人才培养质量。最后,文章提出实施和完善该教学模式的建议,以促进研究生教育的持续改进和发展。