激光推力器液体工质注入系统设计

工质注入系统是液体推进剂激光推力器必不可少的一个组成部分。设计并加工了一套脉冲式液态工质注入系统,解决了工质注入和激光脉冲输出同步的问题;并实现了用相位多普勒粒子分析仪对脉冲式雾化液滴性能参数的测试。     

坦克传动装置润滑系统传动油的流动仿真研究

应用一维流体仿真软件FLOWMASTER2,对坦克传动装置润滑系统的流动进行了模拟,提出了基于FLOWMASTER2软件的传动装置润滑系统的稳态流动仿真模型,并对某型坦克液力机械传动装置润滑系统的流动进行了仿真,预测了润滑系统的流量、流速和压力分布。该研究为坦克及其它车用传动装置润滑系统的流动性能提供了一种有效的理论分析手段和仿真方法。     

Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks

In a master surgery scheduling (MSS) problem, a hospital's operating room (OR) capacity is assigned to different medical specialties. This task is critical since the risk of assigning too much or too little OR time to a specialty is associated with overtime or deficit hours of the staff, deferral or delay of surgeries, and unsatisfied—or even endangered—patients. Most MSS approaches in the literature focus only on the OR while neglecting the impact on downstream units or reflect a simplified version of the real‐world situation. We present the first prediction model for the integrated OR scheduling problem based on machine learning. Our three‐step approach focuses on the intensive care unit (ICU) and reflects elective and urgent patients, inpatients and outpatients, and all possible paths through the hospital. We provide an empirical evaluation of our method with surgery data for Universitätsklinikum Augsburg, a German tertiary care hospital with 1700 beds. We show that our model outperforms a state‐of‐the‐art model by 43% in number of predicted beds. Our model can be used as supporting tool for hospital managers or incorporated in an optimization model. Eventually, we provide guidance to support hospital managers in scheduling surgeries more efficiently.     

垂直刚性面边界条件下水下爆炸气泡运动的理论研究

为研究垂直边界面对水下爆炸气泡脉动的影响,根据势流理论建立了垂直边界面条件下水下爆炸气泡运动的理论模型,编制计算程序进行求解。对水下爆炸气泡脉动运动的特点、流场的速度及压力的分布、气泡引起的载荷形式进行了分析,结果表明,此模型能够反映水下爆炸气泡和周围流体介质的运动规律,并能进行定量的计算。     

批量独立可修件的备件需求预测仿真算法

利用Monte Carlo随机仿真技术,采用事件调度法的仿真策略对可修件的使用与维修过程进行仿真,给出了在给定备件和维修分队数量下批量独立可修件的备件保障概率仿真算法,并用一系列计算实例证明了算法的可行性和正确性,该算法能有效解决安装在不同装备上,具有不同已工作时间、不同故障间隔时间分布、不同修复时间分布的可修件的备件保障概率计算问题,为备件的科学储备提供了有力的决策依据。     

DN150装配式管线涡街流量检测装置研制

涡街流量检测技术是振动式流量仪表中应用最广泛的一种,具有测量范围宽、精度较高、重复性好、可靠性高、不受介质物性和组分变化影响、不需精细过滤、流阻小等一系列优点,特别适合在装配式输油管线上应用.介绍了DN150装配式管线涡街流量检测装置,重点介绍研制中解决的几个关键技术问题.     

Machine scheduling with an availability constraint and job delivery coordination

In this paper we study the scheduling problem that considers both production and job delivery at the same time with machine availability considerations. Only one vehicle is available to deliver jobs in a fixed transportation time to a distribution center. The vehicle can load at most K jobs as a delivery batch in one shipment due to the vehicle capacity constraint. The objective is to minimize the arrival time of the last delivery batch to the distribution center. Since machines may not always be available over the production period in real life due to preventive maintenance, we incorporate machine availability into the models. Three scenarios of the problem are studied. For the problem in which the jobs are processed on a single machine and the jobs interrupted by the unavailable machine interval are resumable, we provide a polynomial algorithm to solve the problem optimally. For the problem in which the jobs are processed on a single machine and the interrupted jobs are nonresumable, we first show that the problem is NP‐hard. We then propose a heuristic with a worst‐case error bound of 1/2 and show that the bound is tight. For the problem in which the jobs are processed on either one of two parallel machines, where only one machine has an unavailable interval and the interrupted jobs are resumable, we propose a heuristic with a worst‐case error bound of 2/3. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Scheduling and lot streaming in two‐machine open shops with no‐wait in process

We study the problem of minimizing the makespan in no‐wait two‐machine open shops producing multiple products using lot streaming. In no‐wait open shop scheduling, sublot sizes are necessarily consistent; i.e., they remain the same over all machines. This intractable problem requires finding sublot sizes, a product sequence for each machine, and a machine sequence for each product. We develop a dynamic programming algorithm to generate all the dominant schedule profiles for each product that are required to formulate the open shop problem as a generalized traveling salesman problem. This problem is equivalent to a classical traveling salesman problem with a pseudopolynomial number of cities. We develop and test a computationally efficient heuristic for the open shop problem. Our results indicate that solutions can quickly be found for two machine open shops with up to 50 products. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Production and transport logistics scheduling with two transport mode choices

This paper considers a new class of scheduling problems arising in logistics systems in which two different transportation modes are available at the stage of product delivery. The mode with the shorter transportation time charges a higher cost. Each job ordered by the customer is first processed in the manufacturing facility and then transported to the customer. There is a due date for each job to arrive to the customer. Our approach integrates the machine scheduling problem in the manufacturing stage with the transportation mode selection problem in the delivery stage to achieve the global maximum benefit. In addition to studying the NP‐hard special case in which no tardy job is allowed, we consider in detail the problem when minimizing the sum of the total transportation cost and the total weighted tardiness cost is the objective. We provide a branch and bound algorithm with two different lower bounds. The effectiveness of the two lower bounds is discussed and compared. We also provide a mathematical model that is solvable by CPLEX. Computational results show that our branch and bound algorithm is more efficient than CPLEX. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Basic scheduling problems with raw material constraints

One of the achievements of scheduling theory is its contribution to practical applications in industrial settings. In particular, taking finiteness of the available production capacity explicitly into account, has been a major improvement of standard practice. Availability of raw materials, however, which is another important constraint in practice, has been largely disregarded in scheduling theory. This paper considers basic models for scheduling problems in contemporary manufacturing settings where raw material availability is of critical importance. We explore single scheduling machine problems, mostly with unit or all equal processing times, and L_max and C_max objectives. We present polynomial time algorithms, complexity and approximation results, and computational experiments. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.