Modelling of grinding mechanics: A review

Grinding is one of the most widely used material removal methods at the end of many process chains. Grinding force is related to almost all grinding parameters, which has a great influence on material removal rate, dimensional and shape accuracy, surface and subsurface integrity, thermodynamics, dynamics, wheel durability, and machining system deformation. Considering that grinding force is related to almost all grinding parameters, grinding force can be used to detect grinding wheel wear, energy calculation, chatter suppression, force control and grinding process simulation. Accurate prediction of grinding forces is important for optimizing grinding parameters and the structure of grinding machines and fixtures. Although there are substantial research papers on grinding mechanics, a comprehensive review on the modeling of grinding mechanics is still absent from the literature. To fill this gap, this work reviews and introduces theoretical methods and applications of mechanics in grinding from the aspects of modeling principles, limitations and possible future trendencies.     

爆炸破片作用下 舰载导弹战斗部的安全性数值模拟

文章主要针对爆炸破片作用下,垂直发射系统中舰载导弹战斗部的安全性进行分析,分别讨论了破片的质量、速度、侵彻角度和破片的数量等因素作用下,舰载导弹外防护设置以及战斗部的响应特性。结果表明:在临界起爆条件附近,炸药的点火增长对撞击速度的变化很敏感。同时,入射角对其是否引爆威胁战斗部的影响也很大;当两破片间距小于破片直径时,破片撞击战斗部形成的冲击波会相互叠加,压力峰值增大,更容易引爆战斗部,而当两破片间距大于1.7倍的破片直径时,此时两破片产生的冲击波叠加效应降低。     

基于量纲分析的弹塑性应力强度因子探讨

以Ⅲ型裂纹(反平面剪切)问题为例，对裂纹尖端弹塑性应力场进行了分析研究。首先，基于断裂力学基本理论，引入弹塑性本构关系，推导弹塑性裂纹尖端场；其次，依据线弹性场中应力强度因子的定义和基于J-积分的弹塑性裂纹尖端应力场的分布，并结合物理意义，定义了与线弹性场应力强度因子一致的弹塑性应力强度因子，来表征弹塑性裂纹尖端应力场的强度；最后，对本文所定义的弹塑性应力强度因子进行了合理性分析，说明了本文定义的适用性。本文所定义的弹塑性应力强度因子，相比于表征弹塑性场的J-积分，具有更明确的物理意义和更简明的表达形式；为弹塑性裂纹尖端场的分析和含裂纹材料弹塑性破坏判据的建立提供了理论方法。另外，本文方式也适合于定义Ⅰ型和Ⅱ型问题。     

基于层次分析法的保障风险评估模型构建与应用

为了快速识别各产品保障过程的薄弱环节，及时制定应对措施，提高外场响应速度，进而提高装备保障能力，依据航空电子产品特点及保障现状，构建了保障压力评估指标体系。在此基础上采用层次分析法，结合历史保障数据，建立了保障能力评估模型。通过模型的应用能够实时评估产品保障风险并预警，为保障资源调度及保障任务规划提供决策支撑。将模型集成到服务保障信息化平台中，实时调用平台中的保障数据并进行风险评估。实践证明，所采用的方法能够有效评估保障风险，显著提高保障决策能力。     

Influence of lunar regolith compressibility on sampling performance of thick wall spiral drills

A 2 m class robotic drill was sent to the Moon and successfully collected and returned regolith samples in late 2020 by China. It was a typical thick wall spiral drill (TWSD) with a hollow auger containing a complex coring system to retain subsurface regolith samples. Before the robotic drill was launched, a series of laboratory tests were carried out to investigate and predict the possible drilling loads it may encounter in the lunar environment. This work presents how the sampling performance of the TWSD is affected by the regolith compressibility. Experiments and analysis during the drilling and sampling process in a simulated lunar regolith environment were conducted. The compressibility of a typical lunar regolith simulant (LRS) was measured through uni-directional compression tests to study the relationship between its inner regolith stress and bulk density. A theoretical model was established to elucidate the cutting discharge behavior by auger flights based on the aforementioned relationship. Experiments were conducted with the LRS, and the results show that the sampling performance is greatly affected by the flux of the drilled cuttings into the spiral flight channels. This work helped in scheduling reasonable drilling parameters to promote the sampling performance of the robotic drill in the Chinese Chang'E 5 mission.     

描述碳纳米管内水分子单链的深度学习势

碳纳米管通道内的受限水具有与体相水截然不同的物理力学性质。当纳米管直径低至约0.8 nm时，通道内水分子形成与生物水通道内类似的单链结构，并显现出极高的流速和离子排斥能力。尽管基于经验势的分子动力学模拟在揭示单链水的奇特行为方面发挥了重要作用，但其模拟结果通常依赖于水模型和壁面-水作用参数选取。本文以从头算分子动力学计算结果为数据集，通过深度神经网络训练获得描述碳纳米管内单链水的深度学习势。基于深度学习势的分子动力学模拟在势能和原子受力方面具有近似第一性原理水平的准确性但低得多的计算成本，能准确重现从头算分子动力学得到的单链水性质，包括O-H键长、H-O-H键角、取向角和密度分布等。此外，本文对比了该深度学习势与常用经典水模型所得结果的异同。本文所构建的深度学习势为以接近第一性原理的准确性进行碳纳米管内单链水体系的大尺寸、长时间模拟提供了可能。     

基于DEA/ANP方法的 声纳浮标搜潜方案决策模型

提出了在反潜巡逻机应召搜潜效能评估中,声纳浮标搜潜方案选择的新方法。首先,根据数据包络分析法(DEA)对方案进行客观性较强的横向评价。然后,由方案构建结构网络化的分析模型。根据网络层次分析法(ANP)的基本理论对模型进行优化,设计面向领域并支持ANP可视化描述与科学决策的工具,并对方案进行主观性较强的纵向比较。结合两次评价结果得到最优的结论。