A multi‐stage stochastic programming approach for network capacity expansion with multiple sources of capacity

In networks, there are often more than one sources of capacity. The capacities can be permanently or temporarily owned by the decision maker. Depending on the nature of sources, we identify the permanent capacity, spot market capacity, and contract capacity. We use a scenario tree to model the uncertainty, and build a multi‐stage stochastic integer program that can incorporate multiple sources and multiple types of capacities in a general network. We propose two solution methodologies for the problem. Firstly, we design an asymptotically convergent approximation algorithm. Secondly, we design a cutting plane algorithm based on Benders decomposition to find tight bounds for the problem. The numerical experiments show superb performance of the proposed algorithms compared with commercial software. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 600–614, 2017     

基于改进LS-SVM的异步电机转子故障诊断

为了提高异步电动机转子故障的诊断精度,给出了一种基于改进最小二乘支持向量机(LS-SVM)的多故障分类算法。首先运用FFT处理电机的定子电流信号得到信号频谱图,从中提取故障特征向量;然后将特征向量送入改进算法进行故障诊断时,在原有多分类算法的基础上引入层次分析法确定故障类别的权重,根据权重值确定故障的诊断顺序,依次进行故障分类。实验表明,改进算法用于故障诊断节省了诊断时间,提高了诊断精度,具有很好的推广前景。     

基于失效树的某型无坐力炮弹储存可靠性分析

通过对某型无坐力炮弹战斗部的结构分析和功能分析,以弹着目标不爆炸为顶事件建立了失效树,并根据该型弹药的功能构件在储存期间的特点选择了失效树的简化原则,建立了系统可靠度模型。确定了由储存因素导致弹着目标不爆炸这一事件的4种主要失效模式。并通过分析其不同的储存期失效机理和影响因素,提出该型炮弹的储存策略。     

基于相关性模型的舰船装备测试性分析与建模

为了提高舰船装备的综合诊断能力,在舰船设计、研制阶段就必须进行装备测试性设计工作。为此,根据舰船装备测试性要求,对装备进行了故障模式影响分析,确定了装备在设计和制造过程中所有可能的故障模式,以及每一故障模式的原因和影响,据此对装备功能和结构进行了划分。然后,利用相关性模型对舰船装备进行测试性分析与建模,建立了舰船装备组成单元的相关性图示模型、数学模型,并运用考虑可靠性和费用的优选方法,建立了舰船装备诊断树,得到舰船装备的测试方案。算例分析表明:该研究可有效提高舰船装备测试的效率,提升测试的经济性。     

油库储油区燃烧爆炸事故树分析

针对油库储油区安全管理点多面广的特点,分析储油区燃烧爆炸事故的相关影响因素和条件,建立完善的事故树模型。通过定性分析理清燃烧爆炸事故与基本事件之间的逻辑关系,定量分析获得各项基本事件的结构重要度排序,找出储油区存在燃烧爆炸隐患的重点部位,制订科学合理的安全信息监控点设置策略,为油库安全管理手段向信息化迈进提供决策依据。     

作战飞机可靠性与维修性仿真模型

通过故障树分析建立了作战飞机仿真逻辑关系。在修正线性同余法的基础上获得了随机数模型。在各设备故障发生状态和修复状态识别的基础上,建立了可靠性维修性仿真模型,确定了作战飞机在仿真过程中的工作状态,并根据故障模式影响分析预计了设备故障对作战飞机的影响。最后以F/A-18为例进行可靠性维修性仿真,获得了实时的故障信息和修复信息,验证了仿真模型的可行性。     

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.     

美国非法证据排除规则与德国证据运用禁止规则之比较

非法获得的证据能否作为定案的依据 ,历来为各国刑事证据理论所关注。美国和德国作为英美法系和大陆法系的典型代表 ,分别确立了非法证据排除规则和证据运用禁止规则。研究了两国排除规则的内涵、发展历史、适用范围及存在差异     

数据挖掘故障诊断专家系统

为了及时准确地对防空导弹飞行试验故障进行诊断,克服传统专家系统获取专家知识的瓶颈,立足于防空导弹飞行试验历史数据,利用数据挖掘的方法获得飞行试验故障模式判定决策树,进而得出导弹故障判定规则,形成故障诊断专家知识库,构建防空导弹故障诊断专家系统.这使数据挖掘和专家系统两者的优点得到充分发挥.     

基于功能树的导弹打击系统目标瞄准点选择方法

针对导弹打击系统目标的问题,建立了基于目标功能损伤度的瞄准点选择方法;在对毁伤树方法进行改进的基础上,提出了描述目标结构与工作流程的目标功能树模型,构造出体现目标整体功能下降的优化目标函数,采用模拟退火算法搜索最优解。通过算例对不同的瞄准点选择方案进行比较,发现考虑目标的功能结构特点时,得到的瞄准点明显优于其它方案。