离子液体润滑剂的金属腐蚀性与抑制

对1-丁基-3-甲基咪唑四氟硼酸盐及1-乙酸乙酯基-3-甲基咪唑四氟硼酸盐两种离子液体润滑剂的金属腐蚀性作了初步研究,发现两种离子液体均对多种金属表面有较强的腐蚀作用,其中含酯基功能化离子液体的腐蚀性相对较小,这是由于其具有较弱的吸湿性和较强的表面吸附能力;另外发现,具有杂环结构的传统防锈剂苯并三氮唑（BTA）能很好地溶解在两种咪唑类离子液体中,并能显著降低两种离子液体对铜的表面腐蚀,说明有望通过利用传统防锈剂抑制离子液体润滑剂对金属的腐蚀作用。     

基于证据理论的自适应协同方法在打击目标排序中的应用

针对指挥员在选择及对打击目标排序时会产生不同结果,采用证据理论进行了协同。以各指挥员的判断作为证据理论的识别框架,采用证据加权法及对各证据的合成,确定了证据的基本可信度分配,降低了各证据间的冲突,筛选出肯定的证据,达成指挥员决策的自适应协同,实现对打击目标更为合理的排序。     

考虑资源共享的维修过程建模及资源配置研究

为研究维修机构资源的优化配置问题,分析了装备维修过程中的多维修小组共享关键资源进行并行维修的特点,采用Petri网技术建立了考虑多维修小组共享检测设备的维修过程模型。应用模型对系统特性进行了定性和定量分析,评价了不同资源配置情况下的维修保障效果。     

电子海图技术在反潜反鱼雷火控设备上的应用

针对反潜反鱼雷火控设备攻击水下来袭目标的作战特点,将电子海图技术应用其中。重点研究了基于电子海图背景的反潜反鱼雷作战态势显示以及辅助指挥决策、快速目标定位、快速目标指示等关键技术,用输入设备提取电子海图信息实现了快速目标定位及快速目标指示功能。研究表明：借助电子海图技术的应用可为反潜武器火控设备有效攻击目标起到积极地作用,对于提升反潜反鱼雷火控设备的作战能力效果明显。     

一种基于预测滤波器的自适应卡尔曼滤波算法

针对系统过程噪声统计特性不确切或未知的条件下,研究了一种基于预测滤波器的自适应卡尔曼滤波算法。由预测滤波器实时估计系统模型误差及其协方差矩阵,再用其修正系统状态预测值及预测误差协方差矩阵,从而自适应调节卡尔曼增益。将该算法应用于弹载SINS/GPS紧耦合组合导航系统并与普通卡尔曼滤波、基于新息的移动开窗自适应卡尔曼滤波进行了对比,仿真结果说明该自适应滤波算法具有更高的可靠性和精度。     

战争设计工程中专家群体研讨组织研究

通过对产生战争复杂性原因的分析,对战争设计工程提出的专家群体集体研讨方法进行了研究;并重点对专家群体组成、在研讨中的作用与专家之间协作关系进行了阐述。为对抗由战争复杂性引起的诸多战争问题,提供了一种切实可行的研究方法。     

基于马尔可夫过程的坦克火力随机对抗模型

根据小规模坦克火力对抗中所具有的马尔可夫性特点,将该过程视为离散状态、离散时间的马尔可夫随机过程(马尔可夫链),由此建立了坦克与反坦克武器系统之间一对一对抗的随机格斗模型,并给出双方获胜概率和平均对抗回合数的计算公式。最后通过实例验证了模型的有效性。该模型克服了轮流对抗不符合战场实际的缺点,为分队指挥员在射击策略的选择和分队火力运用上的快速决策提供了较为精确的量化依据。     

基于案例推理的战争设计工程案例库研究

论述了建设战争设计工程案例库的必要性,就战争设计工程案例结果表示以及案例库建设相关问题进行了初步的探讨,构造了战争设计工程案例框架结构,给出了案例研讨结果的结果序列空间分析模型,建立了基于案例的战争设计工程案例库的案例推理机制。     

Energy‐efficient scheduling for sustainable manufacturing systems with renewable energy resources

Environmentally friendly energy resources open a new opportunity to tackle the problem of energy security and climate change arising from wide use of fossil fuels. This paper focuses on optimizing the allocation of the energy generated by the renewable energy system to minimize the total electricity cost for sustainable manufacturing systems under time‐of‐use tariff by clipping the peak demand. A rolling horizon approach is adopted to handle the uncertainty caused by the weather change. A nonlinear mathematical programming model is established for each decision epoch based on the predicted energy generation and the probability distribution of power demand in the manufacturing plant. The objective function of the model is shown to be convex, Lipchitz‐continuous, and subdifferentiable. A generalized benders decomposition method based on the primal‐dual subgradient descent algorithm is proposed to solve the model. A series of numerical experiments is conducted to show the effectiveness of the solution approach and the significant benefits of using the renewable energy resources.     

Supply chain coordination with product line design and a revenue sharing scheme

Many manufacturers sell their products through retailers and share the revenue with those retailers. Given this phenomenon, we build a stylized model to investigate the role of revenue sharing schemes in supply chain coordination and product variety decisions. In our model, a monopolistic manufacturer serves two segments of consumers, which are distinguished by their willingness to pay for quality. In the scenario with exogenous revenue sharing ratios, when the potential gain from serving the low segment is substantial (e.g., the low‐segment consumers' willingness to pay is high enough or the low segment takes a large enough proportion of the market), the retailer is better off abandoning the revenue sharing scheme. Moreover, when the potential gain from serving the low (high) segment is substantial enough, the manufacturer finds it profitable to offer a single product. Furthermore, when revenue sharing ratios are endogenous, we divide our analysis into two cases, depending on the methods of cooperation. When revenue sharing ratios are negotiated at the very beginning, the decentralized supply chain causes further distortion. This suggests that the central premise of revenue sharing—the coordination of supply chains—may be undermined if supply chain parties meticulously bargain over it.