冲压增程弹进气道设计方法与性能分析

以冲压增程弹为应用背景进行了进气道设计.结合增程弹的特点,讨论了轴对称进气道中心锥参数、喉道参数、外罩参数的选择.特别对进气道唇口处参数、扩张段角度设计方法进行了分析.设计了单锥混压式、单锥外压式以及双锥混压式三种进气道,并进行了数值模拟.分析了进气道主要设计参数对其性能的影响.数值结果表明,就增程弹的性能要求而言,双锥混压式进气道的性能较高.     

脉冲等离子体推力器羽流的粒子模拟

目前微小卫星正在积极地发展中,脉冲等离子体推力器是其推进系统的一个重要发展方向,为了能够将PPT成功地运用于空间,需对其羽流进行研究.将DSMC(Direct Simulation Monte-Carlo)/PIC(Particle in Cell)流体混合算法与一维MHD放电模型相结合,一体化模拟NASA Glenn PPT羽流,对不同出口偏转角的羽流场进行模拟,并与实验结果进行了比较.计算结果显示引入出口速度的偏转角提高了模型的羽流扩散能力,羽流的扩散角是影响羽流的一个主要因素.     

攻角对双三角翼旋涡特性影响的数值模拟

采用数值方法研究了双三角翼上涡流运动随攻角的变化规律.计算取层流假设,研究了攻角在5°～30°,76°/40°后掠双三角翼绕流的流场结构随攻角的变化,并对双三角翼上涡破裂现象对流场结构及气动力性能的影响进行了分析.结果表明,双三角翼上的多涡结构存在强烈的相互影响,较大的攻角会导致涡破裂在翼面上发生,严重影响了双三角翼的气动力性能.     

一种高效的显式模型检验方法

随着软硬件系统规模和功能的不断扩充,状态空间爆炸问题严重影响了模型检验的进一步发展与应用,成为验证大规模系统的瓶颈.在显式模型检验工具Murphi的基础上,针对其可达状态空间组织存在的问题进行改进,提出了基于整型指针与Fibonacci散列的可达状态空间组织方法,实现了一个高效的显式模型检验原型系统,在确保验证正确的同时有效缩短了验证时间,并能在系统规范不可满足的情况下给出反例,有助于系统设计人员快速定位错误.理论分析和实验结果表明了本方法的有效性.     

An attacker‐defender model for analyzing the vulnerability of initial attack in wildfire suppression

Wildfire managers use initial attack (IA) to control wildfires before they grow large and become difficult to suppress. Although the majority of wildfire incidents are contained by IA, the small percentage of fires that escape IA causes most of the damage. Therefore, planning a successful IA is very important. In this article, we study the vulnerability of IA in wildfire suppression using an attacker‐defender Stackelberg model. The attacker's objective is to coordinate the simultaneous ignition of fires at various points in a landscape to maximize the number of fires that cannot be contained by IA. The defender's objective is to optimally dispatch suppression resources from multiple fire stations located across the landscape to minimize the number of wildfires not contained by IA. We use a decomposition algorithm to solve the model and apply the model on a test case landscape. We also investigate the impact of delay in the response, the fire growth rate, the amount of suppression resources, and the locations of fire stations on the success of IA.     

船舶静态电场跟踪的渐进更新扩展卡尔曼滤波器

为了实现利用船舶静态电场对船舶进行跟踪的目的,针对传统卡尔曼滤波算法中存在的问题,设计一种新的非线性滤波器。建立船舶的状态空间模型,分析传统卡尔曼滤波算法在船舶跟踪中存在的问题;依据渐进贝叶斯思想,利用连续白噪声与离散白噪声序列噪声协方差之间的关系,设计一种新的渐进更新扩展卡尔曼滤波器。仿真结果表明,该滤波器能有效地抑制由于初始误差较大而造成的滤波性能下降和滤波发散,能够有效地跟踪船舶,具有较高的实用价值。     

柔软物体力触觉形变模型验证系统

为了验证柔性物体力-形变模型的合理性,构建了基于CC2531芯片的无线数据收发平台、力传感器测量平台和FALCON手控器位移测量平台的力-形变模型验证系统。以新鲜猪肝脏为实验对象,研究了弹性形变实验和穿刺实验的作用力与位移之间的关系;以力-形变测量数据为基础,进行了参数验证校调。仿真实验结果表明:模型中力-形变特性与实际测量值保持一致。该系统能广泛应用于柔性物体力-形变模型验证,对于促进力触觉虚拟医学仿真系统的发展具有重要意义。     

掠飞末敏弹耦合运动动导数计算

以新型掠飞末敏弹为研究对象,提出了基于欧拉转动定理和滑移网格技术的复杂角运动模拟方法,利用著名的罗德里格斯转换矩阵插值求得弹箭在每个时间步的角速度修正值,并指定给球形滑移网格区。通过对非定常气动参数进行求解辨识,分析了不同马赫数下掠飞末敏弹滚转运动对其俯仰组合动导数和升力系数动导数的影响规律。结果表明:所提角运动模拟方法可有效消除姿态角计算的累积误差,实现对弹箭任意给定角运动的准确模拟;弹箭滚转运动对俯仰组合导数和升力系数动导数的辨识结果均存在显著影响,在进行弹箭动导数计算和稳定性分析时需充分考虑俯仰耦合效应的影响。     

Value management of diagnostic equipment with cancelation,no‐show,and emergency patients

Magnetic resonance imaging and other multifunctional diagnostic facilities, which are considered as scarce resources of hospitals, typically provide services to patients with different medical needs. This article examines the admission policies during the appointment management of such facilities. We consider two categories of patients: regular patients who are scheduled in advance through an appointment system and emergency patients with randomly generated demands during the workday that must be served as soon as possible. According to the actual medical needs of patients, regular patients are segmented into multiple classes with different cancelation rates, no‐show probabilities, unit value contributions, and average service times. Management makes admission decisions on whether or not to accept a service request from a regular patient during the booking horizon to improve the overall value that could be generated during the workday. The decisions should be made by considering the cancelation and no‐show behavior of booked patients as well as the emergency patients that would have to be served because any overtime service would lead to higher costs. We studied the optimal admission decision using a continuous‐time discrete‐state dynamic programming model. Identifying an optimal policy for this discrete model is analytically intractable and numerically inefficient because the state is multidimensional and infinite. We propose to study a deterministic counterpart of the problem (i.e., the fluid control problem) and to develop a time‐based fluid policy that is shown to be asymptotically optimal for large‐scale problems. Furthermore, we propose to adopt a mixed fluid policy that is developed based on the information obtained from the fluid control problem. Numerical experiments demonstrate that this improved policy works effectively for small‐scale problems. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 287–304, 2016     

云模型改进惯性权重的混沌交替粒子群算法

标准粒子群算法通过线性减小惯性权重系数来调整寻优性能,但缺乏智能化机制易导致算法后期产生早熟或陷入局部最优而产生僵局。针对这一问题,提出一种基于云模型改进惯性权重的混沌交替粒子群优化算法。根据粒子迭代变化关系,采用云模型理论对惯性权重ω进行智能化调整,以平衡其全局和局部搜索能力,防止算法产生局部僵局;另外,判定粒子稳定性,对于可能陷入局部僵局的稳定粒子进行混沌扰动,促使其跳出僵局进而向最优位置更新。实验与分析表明,基于云模型改进惯性权重的混沌交替粒子群优化算法能够跳出局部僵局且具有较高的寻优精度,算法接近完全收敛时的平均迭代次数,较现有相关研究分别降低了13.73%~20.11%。