Fragment spatial distribution of prismatic casing under internal explosive loading

Non-cylindrical casings filled with explosives have undergone rapid development in warhead design and explosion control. The fragment spatial distribution of prismatic casings is more complex than that of traditional cylindrical casings. In this study, numerical and experimental investigations into the fragment spatial distribution of a prismatic casing were conducted. A new numerical method, which adds the Lagrangian marker points to the Eulerian grid, was proposed to track the multi-material interfaces and material dynamic fractures. Physical quantity mappings between the Lagrangian marker points and Eulerian grid were achieved by their topological relationship. Thereafter, the fragment spatial distributions of the prismatic casing with different fragment sizes, fragment shapes, and casing geometries were obtained using the numerical method. Moreover, fragment spatial distribution experiments were conducted on the prismatic casing with different fragment sizes and shapes, and the experimental data were compared with the numerical results. The effects of the fragment and casing geometry on the fragment spatial distributions were determined by analyzing the numerical results and experimental data. Finally, a formula including the casing geometry parameters was fitted to predict the fragment spatial distribution of the prismatic casing under internal explosive loading.     

Dynamic pricing in a trade-in program with replacement and new customers

Trade-in programs have been widely adopted to enhance repeat purchase from replacement customers. Considering that a market consists of replacement and new segments, we study the joint and dynamic decisions on the selling price of new product (hereafter, “selling price”) and the trade-in price involved in the program. By adopting a vertical product differentiation choice model, we investigate two scenarios in this paper. In the base model, the manufacturer has sufficiently large production capacity to fulfill the customer demand. We characterize the structural properties of the joint pricing decisions and compare them with the optimal pricing policy under regular selling. We further propose a semi-dynamic trade-in program, under which the new product is sold at a fixed price and the trade-in price can be adjusted dynamically. Numerical experiments are conducted to evaluate the performance of the dynamic and semi-dynamic trade-in programs. In an extended model, we consider the scenario in which the manufacturer stocks a batch of new products in the beginning of the selling horizon and the inventory cannot be replenished. Following a revenue management framework, we characterize the structural properties with respect to time period and inventory level of new products.     

Spatial pricing and product allocation in online retailing

Spatial pricing means a retailer price discriminates its customers based on their geographic locations. In this article, we study how an online retailer should jointly allocate multiple products and facilitate spatial price discrimination to maximize profits. When deciding between a centralized product allocation ((i.e., different products are allocated to the same fulfillment center) and decentralized product allocation (ie, different products are allocated to different fulfillment centers), the retailer faces the tradeoff between shipment pooling (ie, shipping multiple products in one package), and demand localization (ie, stocking products to satisfy local demand) based on its understanding of customers' product valuations. In our basic model, we consider two widely used spatial pricing policies: free on board (FOB) pricing that charges each customer the exact amount of shipping cost, and uniform delivered (UD) pricing that provides free shipping. We propose a stylized model and find that centralized product allocation is preferred when demand localization effect is relatively low or shipment pooling benefit is relatively high under both spatial pricing policies. Moreover, centralized product allocation is more preferred under the FOB pricing which encourages the purchase of virtual bundles of multiple products. Furthermore, we respectively extend the UD and FOB pricing policies to flat rate shipping (ie, the firm charges a constant shipping fee for each purchase), and linear rate shipping (ie, the firm sets the shipping fee as a fixed proportion of firm's actual fulfillment costs). While similar observations from the basic model still hold, we find the firm can improve its profit by sharing the fulfillment cost with its customers via the flat rate or linear rate shipping fee structure.     

Pricing and capacity allocation strategies: Implications for manufacturers with product sharing

Emerging sharing modes, like the consumer-to-consumer (C2C) sharing of Uber and the business-to-consumer (B2C) sharing of GoFun, have considerably affected the retailing markets of traditional manufacturers, who are motivated to consider product sharing when making pricing and capacity decisions, particularly electric car manufacturers with limited capacity. In this paper, we examine the equilibrium pricing for a capacity-constrained manufacturer under various sharing modes and further analyze the impact of capacity constraint on the manufacturer's sharing mode selection as well as equilibrium outcomes. We find that manufacturers with low-cost products prefer B2C sharing while those with high-cost products prefer C2C sharing except when the sharing price is moderate. However, limited capacity motivates manufacturers to enter into the B2C sharing under a relatively low sharing price, and raise the total usage level by sharing high-cost products. We also show that the equilibrium capacity allocated to the sharing market with low-cost products first increases and then decreases. Finally, we find that sharing low-cost products with a high limited capacity leads to a lower retail price under B2C sharing, which creates a win-win situation for both the manufacturer and consumers. However, sharing high-cost products with a low limited capacity creates a win-lose situation for them.     

Dynamic pricing and matching in ride-hailing platforms

Ride-hailing platforms such as Uber, Lyft, and DiDi have achieved explosive growth and reshaped urban transportation. The theory and technologies behind these platforms have become one of the most active research topics in the fields of economics, operations research, computer science, and transportation engineering. In particular, advanced matching and dynamic pricing (DP) algorithms—the two key levers in ride-hailing—have received tremendous attention from the research community and are continuously being designed and implemented at industrial scales by ride-hailing platforms. We provide a review of matching and DP techniques in ride-hailing, and show that they are critical for providing an experience with low waiting time for both riders and drivers. Then we link the two levers together by studying a pool-matching mechanism called dynamic waiting (DW) that varies rider waiting and walking before dispatch, which is inspired by a recent carpooling product Express Pool from Uber. We show using data from Uber that by jointly optimizing DP and DW, price variability can be mitigated, while increasing capacity utilization, trip throughput, and welfare. We also highlight several key practical challenges and directions of future research from a practitioner's perspective.     

无衍射艾里光束的横向自加速特性

无衍射艾里光束的横向自加速特性使得光束在自由空间沿弯曲路径进行传输成为可能。利用一维傍轴波动方程对新型无衍射艾里光束的横向自加速特性进行了仿真研究。研究表明,当入射波长一定时,艾里光束的横向加速度大小与传播距离呈正比关系,而与任意横向尺度的大小呈反比关系。同时,利用波印廷矢量对艾里光束横向自加速的内在机理进行了研究。最后,利用通用型液晶空间光调制器对二维艾里光束的产生和横向自加速特性进行了实验研究,所得结果与仿真计算结果取得了较好的一致性。     

Dynamic pricing and replenishment: Optimality,bounds, and asymptotics

In many applications, managers face the problem of replenishing and selling products during a finite time horizon. We investigate the problem of making dynamic and joint decisions on product replenishment and selling in order to improve profit. We consider a backlog scenario in which penalty cost (resulting from fulfillment delay) and accommodation cost (resulting from shortage at the end of the selling horizon) are incurred. Based on continuous‐time and discrete‐state dynamic programming, we study the optimal joint decisions and characterize their structural properties. We establish an upper bound for the optimal expected profit and develop a fluid policy by resorting to the deterministic version of the problem (ie, the fluid problem). The fluid policy is shown to be asymptotically optimal for the original stochastic problem when the problem size is sufficiently large. The static nature of the fluid policy and its lack of flexibility in matching supply with demand motivate us to develop a “target‐inventory” heuristic, which is shown, numerically, to be a significant improvement over the fluid policy. Scenarios with discrete feasible sets and lost‐sales are also discussed in this article.     

空间信息支持高能激光武器应用研究*

依据空间信息支持现代作战的主要内容,介绍了五大类空间信息状况,分析了新概念武器高能激光的基本原理,并就其应用过程建立了UML模型。在此基础上,设计了空间信息支持高能激光武器应用系统的框架,并就高能激光武器对空间信息的需求进行了重点分析,而后以信息的转换与传递为主线,探讨了高能激光武器运用空间信息的流程。最后对该领域研究的趋势和发展前景做出了展望,并提出对其未来发展的要求。     

C3I系统中战术态势估计的推理方法

本文首先讨论了态势估计中推理框架的现有形式，并从中抽取共性；然后讨论了推理算法的研究现状及存在的问题；最后在推理框架共性之下，提出了应用模糊理论和统计理论解决这些问题的步骤。     

X-2000空间数据库系统的设计和实现

空间数据库技术是地理信息系统（ＧｅｏｇｒａｐｈｉｃＩｎｆｏｒｍａｔｉｏｎＳｙｓｔｅｍ，简称ＧＩＳ）的核心技术。我们设计和实现了一个新型的空间数据库系统——Ｘ－２０００空间数据库系统，它综合利用了空间数据库的新技术，提出了新的空间数据库的组织方法。本文重点介绍该空间数据库系统的设计思路和实现方法。