空降兵装备发展仿真实验研究

开展空降兵装备发展仿真实验研究,是促进空降兵装备快速发展的有效途径。提出了空降兵装备发展实验研究体系结构,在此基础上,重点对仿真实验研究的技术框架和模型体系的柔性设计进行了分析与研究,并对发展需求论证环境和作战运用研究环境的部署与运行方式进行了阐述,旨在为空降兵装备发展仿真实验研究的顶层设计及具体实现提供参考。     

基于技术规范视角的重庆大型商业建筑设计防火规范的制定

从技术规范的辩证视角出发,提出重庆《大型商业建筑设计防火规范》修订的全程性、综合性、辩证性及实践性原则。基于重庆市现有大型商业建筑营业面积、人员密度等数据,运用统计学工具,借鉴国内外标准,在保证防火安全性能的前提下,统筹考虑重庆大型商业建筑的地方特点,在人员密度、室内商业步行街设计及消防设施强化等方面,科学定量,适度超前,科学制定新防火设计规范,并给出了规范的主要内容。为建筑防火设计规范的制定和修订,提供了思路。     

谈消防控制室的消防安全整体解决方案

消防控制室是建（构）筑物消防设施的控制、指挥、调度枢纽,是消防设施核心中的核心,直接决定能否尽早发现火灾、全面控制火灾、成功扑救火灾、组织迅速疏散。从设计、施工、使用三个方面系统阐述了消防控制室存在的常见问题及解决方案,以期科学、安全、合理地发挥消防控制室的各项功能。     

ISAR雷达欺骗式干扰信号生成算法

宽带ISAR雷达能够从目标回波中计算得出众多目标特征,对ISAR雷达的干扰信号必须高逼真地模拟目标的电磁散射特性和运动特性。从弹头目标电磁散射机理出发,分析了干扰信号生成流程,提出二维成像干扰的实现方案。针对虚假目标特性模拟问题,提出基于一维距离像模板合成欺骗干扰信号的算法。算法采用距离像模板与实际宽带ISAR信号的卷积调制处理,生成的干扰信号能较好地反映目标的电磁特性。通过多个脉冲的模拟,生成的干扰信号也能够准确反映目标的运动特性。仿真实验对暗室测量数据和HRRP模板数据进行成像效果对比,验证了算法的有效性。该算法对二维成像干扰机的工程设计具有指导意义。     

Halo轨道的航天器编队构型设计

针对不同干涉基线约束下的最优Halo轨道编队构型设计方法展开研究。以Richardson关于Halo轨道的三阶近似解析解为基础建立同一轨道上两航天器编队的相对运动学模型;以平动点为质心的旋转坐标系为基准构造与编队主航天器和观测目标相关的旋转坐标系,并在此坐标系中给出不同于二体问题的干涉基线计算方法;以满足基线约束下观测时间最长为目标给出最优编队构型设计方法。最后,以绕日-地L2点的Halo轨道为例对上述编队构型设计方法的有效性进行了仿真验证。     

防暴发射器身管长度优化研究

为解决某型防暴发射器身管设计不合理导致有效射程短的问题,以仿真设计的方法,运用Matlab计算软件对其进行了内弹道模拟仿真,获得了不同身管长度下该防暴发射器的膛压和速度曲线,确定了最优身管长度。然后利用ANsYs有限元分析软件,对延长身管后的模型进行了强度校核。仿真结果和实弹数据表明：防暴发射器身管长度设计合理,有效提高了其实际射程和作战效能,研究工作优化了防暴发射器的设计。     

基于UML的导弹伺服测试系统通用设计方法

分析了导弹伺服测试系统组成及功能,采用UML静态建模技术构建了导弹伺服测试系统设计的需求描述模型,运用动态建模方法建立了系统结构模型和行为模型,并以上述模型为基础,设计了导弹伺服测试系统通用软硬件结构。该方法优化了导弹伺服测试系统共性设计,并创建了特性模型架构和特化接口,有效提高了系统的设计效率和开发质量。     

Minimum violations and predictive meta‐rankings for college football

This article presents two meta‐ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systems—a combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out‐of‐sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum; the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near‐optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17–33, 2014     

Choosing arrival process models for service systems: Tests of a nonhomogeneous Poisson process

Service systems such as call centers and hospital emergency rooms typically have strongly time‐varying arrival rates. Thus, a nonhomogeneous Poisson process (NHPP) is a natural model for the arrival process in a queueing model for performance analysis. Nevertheless, it is important to perform statistical tests with service system data to confirm that an NHPP is actually appropriate, as emphasized by Brown et al. [8]. They suggested a specific statistical test based on the Kolmogorov–Smirnov (KS) statistic after exploiting the conditional‐uniform (CU) property to transform the NHPP into a sequence of i.i.d. random variables uniformly distributed on [0,1] and then performing a logarithmic transformation of the data. We investigate why it is important to perform the final data transformation and consider what form it should take. We conduct extensive simulation experiments to study the power of these alternative statistical tests. We conclude that the general approach of Brown et al. [8] is excellent, but that an alternative data transformation proposed by Lewis [22], drawing upon Durbin [10], produces a test of an NHPP test with consistently greater power. We also conclude that the KS test after the CU transformation, without any additional data transformation, tends to be best to test against alternative hypotheses that primarily differ from an NHPP only through stochastic and time dependence. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 66–90, 2014     

The impact of operational decisions on the design of salesforce incentives

When facing high levels of overstock inventories, firms often push their salesforce to work harder than usual to attract more demand, and one way to achieve that is to offer attractive incentives. However, most research on the optimal design of salesforce incentives ignores this dependency and assumes that operational decisions of production/inventory management are separable from design of salesforce incentives. We investigate this dependency in the problem of joint salesforce incentive design and inventory/production control. We develop a dynamic Principal‐Agent model with both Moral Hazard and Adverse Selection in which the principal is strategic and risk‐neutral but the agent is myopic and risk‐averse. We find the optimal joint incentive design and inventory control strategy, and demonstrate the impact of operational decisions on the design of a compensation package. The optimal strategy is characterized by a menu of inventory‐dependent salesforce compensation contracts. We show that the optimal compensation package depends highly on the operational decisions; when inventory levels are high, (a) the firm offers a more attractive contract and (b) the contract is effective in inducing the salesforce to work harder than usual. In contrast, when inventory levels are low, the firm can offer a less attractive compensation package, but still expect the salesforce to work hard enough. In addition, we show that although the inventory/production management and the design of salesforce compensation package are highly correlated, information acquisition through contract design allows the firm to implement traditional inventory control policies: a market‐based state‐dependent policy (with a constant base‐stock level when the inventory is low) that makes use of the extracted market condition from the agent is optimal. This work appears to be the first article on operations that addresses the important interplay between inventory/production control and salesforce compensation decisions in a dynamic setting. Our findings shed light on the effective integration of these two significant aspects for the successful operation of a firm. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 320–340, 2014