Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

An interface shear damage model of chromium coating/steel substrate under thermal erosion load

The Cr-plated coating inside a gun barrel can effectively improve the barrel's erosion resistance and thus increase the service life.However,due to the cyclic thermal load caused by high-temperature gun-powder,micro-element damage tends to occur within the Cr coating/steel substrate interface,leading to a gradual deterioration in macro-mechanical properties for the material in the related region.In order to mimic this cyclic thermal load and,thereby,study the thermal erosion behavior of the Cr coating on the barrel's inner wall,a laser emitter is utilized in the current study.With the help of in-situ tensile test and finite element simulation results,a shear stress distribution law of the Cr coating/steel substrate and a change law of the interface ultimate shear strength are identified.Studies have shown that the Cr coating/steel substrate interface's ultimate shear strength has a significant weakening effect due to increasing temperature.In this study,the interfacial ultimate shear strength decreases from 2.57 GPa(no erosion)to 1.02 GPa(laser power is 160 W).The data from this experiment is employed to establish a Cr coating/steel substrate interface shear damage model.And this model is used to predict the flaking process of Cr coating by finite element method.The simulation results show that the increase of coating crack spacing and coating thickness will increase the service life of gun barrel.     

XNAV中的相对论效应(III)——时空测量值的坐标转换

在文献[1-3]中求得的XNAV基本方程中,时间和距离是指太阳质心系(BCRS)中的坐标量。但在实际测量中,接收机测量的时间是时钟的固有时,接收机的位置一般应以地心系(GCRS)为基准。在相对论框架内完成这两个坐标转换,使得XNAV测量方程能够直接得到应用。最后给出了完整的XNAV高精度测量方程及其在实际测量中的计算过程。     

时敏打击指挥控制技术初探

分析了时敏目标打击链,介绍了压缩打击链的主要途径,描述了图像处理、战场数据管理、武器动态分配、智能代理集成等有关时敏打击指挥控制技术,为时敏打击指挥控制系统的研究提供参考。     

基于时域平均的齿轮故障诊断

提出了信号时域平均处理的新算法,解决了周期截断误差对平均结果的影响,并对测取的齿轮箱齿轮故障振动信号进行了处理。实验结果表明:该方法在齿轮故障信号的处理中能够消除背景噪声的影响,取得比较理想的效果。     

非自伴情形下时滞抛物方程的惯性流形

利用Lyapunov-Perron方法在适当的谱间隙条件和适当小的时滞假设下,证明了一类非自伴算子情形下半线性时滞抛物方程惯性流形的存在性。     

A stochastic model for burn‐in procedures in accelerated environment

Burn‐in procedure is a manufacturing technique that is intended to eliminate early failures of system or product. Burning‐in a component or system means to subject it to a period of use prior to being used in field. Generally, burn‐in is considered expensive and so the length of burn‐in is typically limited. Thus, burn‐in is most often accomplished in an accelerated environment in order to shorten the burn‐in process. A new failure rate model for an accelerated burn‐in procedure, which incorporates the accelerated ageing process induced by the accelerated environmental stress, is proposed. Under a more general assumption on the shape of failure rate function of products, which includes the traditional bathtub‐shaped failure rate function as a special case, upper bounds for optimal burn‐in time will be derived. A numerical example will also be given for illustration. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Transient analysis of Markov models of fault‐tolerant systems with deferred repair using split regenerative randomization

The (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well‐controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability‐like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C₂, including typical failure/repair reliability‐like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and, for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C₂ model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization‐based methods. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

Better is the Neighbor?

Abstract

This study applies the Sequential Panel Selection Method (SPSM), to investigate the convergence properties of the military expenditure of the North Atlantic Treaty Organization (NATO) during the period of 1990–2015. Compared to the traditional methods, SPSM considers fundamentally general spatial homogeneous and heterogeneous relationships with countries and examines the evolution of military expenditure. We find that four-fifths of NATO member countries have been convergent with the UK, but no country’s military expenditure is convergent with the US. This means that there is no significant linkage effect in the US for NATO military expenditure. While they are allies of the US, the majority of NATO member countries’ military expenditures are consistent with UK military expenditure. The main reasons are due to the geographical space layout and the international relationship convergence. The results indicate that more than four-fifths of NATO member countries have been coordinated with convergence theory and spillover effect.     

基于最短拦截时间的异面拦截机动轨道设计与优化

本文构建了单脉冲机动在燃耗约束下的最短时间拦截轨道设计模型与求解方法,将用数学泛函求边值问题转换为高次代数方程的求解计算,并用牛顿迭代法进行快速寻根,仿真结果表明模型及算法准确、有效,满足精度要求。