Hypersonic impact flash characteristics of a long-rod projectile collision with a thin plate target

Impact flash occurs when objects collide at supersonic speeds and can be used for real-time damage assessment when weapons rely on kinetic energy to destroy targets.However,the mechanism of impact flash remains unclear.A series of impact flash experiments of flat-head long-rod projectiles impacting thin target plates were performed with a two-stage light gas gun.The impact flash spectra for 6061 aluminum at 1.3-3.2 km/s collision speeds were recorded with a high-speed camera,a photoelectric sensor,and a time-resolved spectrometer.The intensity of the impact flash exhibited a pulse charac-teristic with time.The intensity(I)increased with impact velocity(V0)according to I∝Vn0,where n = 4.41 for V0 ＞ 2 km/s.However,for V0 ＜ 2 km/s,n = 2.21,and the intense flash duration is an order of magnitude less than that of higher V0.When V0 ＞ 2 km/s,a continuous spectrum(thermal radiation background)was observed and increased in intensity with V0.However,for V0 ＜ 2 km/s,only atomic line spectra were detected.There was no aluminum spectral lines for V0 ＜ 2 km/s,which indicated that it had not been vaporized.The initial intense flash was emission from excited and ionized ambient gases near the impact surface,and had little relationship with shock temperature rise,indicating a new mechanism of impact flash.     

Numerical investigation on cooling performance of filter in a pyrotechnic gas generator

As a key part of the pyrotechnic gas generator,the filter not only removes the particulate matter but also cools the hot gas to a safe level.This paper aims to improve the understanding of the basic heat and flow phenomenon in the gas generator.The pyrotechnic gas generator is modelling by a simplified filter structure with fiber arrays.A finite-volume model of the heat and fluid flow is proposed to simulate the detailed multi-dimensional flow and energy conversion behaviors.Several verification results are in good agreement with data in different references.Simulation results demonstrate that the filter can not only absorb heat from the gas but also cause the high intensity enhancement of the heat transfer.The per-formance difference between inline and staggered arrays is also discussed.The findings of the study put a further prediction tool for the understanding and design of the filter system with fibers.     

Research and development on hypervelocity impact protection using Whipple shield: An overview

Whipple shield, a dual-wall system, as well as its improved structures, is widely applied to defend the hypervelocity impact of space debris (projectile). This paper reviews the studies about the mechanism and process of protection against hypervelocity impacts using Whipple shield. Ground-based experiment and numerical simulation for hypervelocity impact and protection are introduced briefly. Three steps of the Whipple shield protection are discussed in order, including the interaction between the projectile and bumper, the movement and diffusion of the debris cloud, and the interaction between the debris cloud and rear plate. Potential improvements of the protection performance focusing on these three steps are presented. Representative works in the last decade are mentioned specifically. Some prospects and suggestions for future studies are put forward.     

基于自适应Kalman滤波算法的航空发动机可测参数及其偏离量估计

针对采用估计可测参数偏离量建立航空发动机机载自适应模型的方案中,可测参数偏离量估计的问题,引入了CA(Constant Acceleration)模型,建立了简化的可测参数状态方程和测量方程,采用自适应Kalman滤波算法直接估计可测参数,由估计出的可测参数与发动机非线性模型计算的额定值之差,获得可测参数偏离量.为解决因简化的状态模型系统误差较大,采用标准Kalman滤波会出现估计严重偏离真值的问题,分析了标准Kalman滤波准则和状态模型误差对滤波结果的影响,采用动态调整状态预报在滤波估计结果中权重的策略,给出了单因子自适应Kalman滤波算法准则及递推公式,使滤波估计准确.对不同的可测参数分别采取序列滤波的方法,减少了运算量.以仿真产生的发动机测量数据为例,对系统模型和所设计的算法进行验证,计算结果表明,所设计的滤波算法具有很快的收敛速度和计算速度,结果优于标准Kalman滤波算法,具有更好的估计精度和一定的工程应用价值.     

A stochastic machine maintenance and sale problem: Results with different production functions

In this article we solve and analyze a stochastic version of the Boiteux problem by employing the stochastic optimal control method. Our setup is close to that of Thompson [22]. Our focus is to analyze, under the same structure, how different production functions and how the variance in machine deterioration/maintenance affect our optimal machine maintenance and sale date decisions. © 1993 John Wiley & Sons, Inc.     

Allocation of quality improvement targets based on investments in learning

Purchased materials often account for more than 50% of a manufacturer's product nonconformance cost. A common strategy for reducing such costs is to allocate periodic quality improvement targets to suppliers of such materials. Improvement target allocations are often accomplished via ad hoc methods such as prescribing a fixed, across‐the‐board percentage improvement for all suppliers, which, however, may not be the most effective or efficient approach for allocating improvement targets. We propose a formal modeling and optimization approach for assessing quality improvement targets for suppliers, based on process variance reduction. In our models, a manufacturer has multiple product performance measures that are linear functions of a common set of design variables (factors), each of which is an output from an independent supplier's process. We assume that a manufacturer's quality improvement is a result of reductions in supplier process variances, obtained through learning and experience, which require appropriate investments by both the manufacturer and suppliers. Three learning investment (cost) models for achieving a given learning rate are used to determine the allocations that minimize expected costs for both the supplier and manufacturer and to assess the sensitivity of investment in learning on the allocation of quality improvement targets. Solutions for determining optimal learning rates, and concomitant quality improvement targets are derived for each learning investment function. We also account for the risk that a supplier may not achieve a targeted learning rate for quality improvements. An extensive computational study is conducted to investigate the differences between optimal variance allocations and a fixed percentage allocation. These differences are examined with respect to (i) variance improvement targets and (ii) total expected cost. For certain types of learning investment models, the results suggest that orders of magnitude differences in variance allocations and expected total costs occur between optimal allocations and those arrived at via the commonly used rule of fixed percentage allocations. However, for learning investments characterized by a quadratic function, there is surprisingly close agreement with an “across‐the‐board” allocation of 20% quality improvement targets. © John Wiley & Sons, Inc. Naval Research Logistics 48: 684–709, 2001     

救生伞背带分系统对假人动载的影响

为了改善救生伞背带分系统的安全性,建立降落伞-背带-假人系统的动力学模型,分析背带及脱离锁参数对假人质心过载的影响。针对救生伞假人高速开伞空投试验,采用多体动力学方法建立降落伞、背带脱离锁和假人的十五自由度动力学模型;采用半质量-阻尼弹簧模型建立背带模型,连接降落伞、脱离锁和假人;利用实测过载计算降落伞开伞力。利用所建立的动力学模型仿真典型状态下假人和背带的动力学响应,验证所建立模型的合理性。分析了脱离锁位置、背带松紧程度、背带材料特性对假人质心最大过载的影响,可用于指导背带设计以及确定最佳的背带脱离锁位置。     

Parallel machine scheduling with batch deliveries to minimize total flow time and delivery cost

Motivated by the flow of products in the iron and steel industry, we study an identical and parallel machine scheduling problem with batch deliveries, where jobs finished on the parallel machines are delivered to customers in batches. Each delivery batch has a capacity and incurs a cost. The objective is to find a coordinated production and delivery schedule that minimizes the total flow time of jobs plus the total delivery cost. This problem is an extension of the problem considered by Hall and Potts, Ann Oper Res 135 (2005) 41–64, who studied a two‐machine problem with an unbounded number of transporters and unbounded delivery capacity. We first provide a dynamic programming algorithm to solve a special case with a given job assignment to the machines. A heuristic algorithm is then presented for the general problem, and its worst‐case performance ratio is analyzed. The computational results show that the heuristic algorithm can generate near‐optimal solutions. Finally, we offer a fully polynomial‐time approximation scheme for a fixed number of machines. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 492–502, 2016     

舰船装备价格指数与物价指数的关系研究

对舰船装备价格指数与物价指数建立数学模型 ,主要分析物价指数对舰船各项成本的影响 ,分析舰船装备价格指数比物价指数涨幅更大的原因 .     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.