低雷诺数壁面约束流动皮托管测速误差分析与校正

针对低雷诺数壁面约束流动中皮托管测速误差产生的两大主要影响因素——剪切速度与近壁效应,采用计算流体力学技术分别对其进行数值模拟,并研究各自引起的误差变化规律。数值模拟结果表明:虽然剪切速度引起的流线偏移规律与相关文献结论基本一致,但是数值结果预测的流线偏移量并不是一个渐近函数;近壁距离在5倍管径即出现较为明显的测量误差,并且发现近壁距离在1倍管径处出现误差的非单调性变化。最后通过将数值模拟结果与现有的修正方法进行对比,提出了更为合理的修正方程。     

Inventory policies for a make‐to‐order system with a perishable component and fixed ordering cost

We consider a make‐to‐order production system where two major components, one nonperishable (referred to as part 1) and one perishable (part 2), are needed to fulfill a customer order. In each period, replenishment decisions for both parts need to be made jointly before demand is realized and a fixed ordering cost is incurred for the nonperishable part. We show that a simple (s_n,S,S) policy is optimal. Under this policy, S along with the number of backorders at the beginning of a period if any and the availability of the nonperishable part (part 1) determines the optimal order quantity of the perishable part (part 2), while (s_n,S) guide when and how much of part 1 to order at each state. Numerical study demonstrates that the benefits of using the joint replenishment policy can be substantial, especially when the unit costs are high and/or the profit margin is low. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

French Arms Exports and Intrastate Conflicts: An Empirical Investigation

The aim of this article is to evaluate how French Major Conventional Weapons (MCW) exports impact on the conflict intensity of recipient countries. The recent increase in French arms exports seems to contradict the French political discourse on the promotion of regional stability. We run zero-inflated ordered probit model in order to analyze the role of the arms trade on the intensity of civil conflicts in 144 countries from 1992 to 2014, using SIPRI and UCDP/PRIO data. Our results suggest that French MCW exports tended not to exacerbate intrastate conflicts during this period. This finding is robust to changes in the empirical framework. We propose two lines of explanations: France seems to be prone to choosing partners that respect human rights and selling more ‘defense-oriented’ MCW than the rest of the world.     

Joining by Number: Military Intervention in Civil Wars

Understanding why and when states militarily intervene in civil wars is crucial. Intervention can increase civil wars’ severity and the strategies employed in civil wars are shaped by the possibility of military intervention. This article argues that potential military interveners react to information revealed about warring parties’ intentions and relative power. Without revealed information, potential military interveners are unlikely to reconsider their initial decision to remain out of the war. Revealed information causes non-belligerent states to update their expectations about the trajectory of the civil war causing them, at times, to change their calculus about the benefits of belligerency and thus intervene. This helps explain why civil wars spread and when they do so. This explanation is tested using generalised estimating equations on a new data-set of unexpected events for the civil wars in the Correlates of War Intrastate War and PRIO Armed Conflict data-sets.     

An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations

Unmanned aerial vehicles (UAVs), increasingly vital to the success of military operations, operate in a complex and dynamic environment, sometimes in concert with manned aircraft. We present an extensible modeling framework for the solution to the dynamic resource management (DRM) problem, where airborne resources must be reassigned to time‐sensitive tasks in response to changes in battlespace conditions. The DRM problem is characterized by diverse tasks with time windows, heterogeneous resources with fuel‐ and payload‐capacity limitations, and multiple competing objectives. We propose an integer linear programing formulation for this problem, where mathematical feasibility is guaranteed. Although motivated by airborne military operations, the proposed general modeling framework is applicable to a wide array of settings, such as disaster relief operations. Additionally, land‐ or water‐based operations may be modeled within this framework, as well as any combination of manned and unmanned vehicles. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

Dynamic pricing and inventory control with learning

Optimal operating policies and corresponding managerial insight are developed for the decision problem of coordinating supply and demand when (i) both supply and demand can be influenced by the decision maker and (ii) learning is pursued. In particular, we determine optimal stocking and pricing policies over time when a given market parameter of the demand process, though fixed, initially is unknown. Because of the initially unknown market parameter, the decision maker begins the problem horizon with a subjective probability distribution associated with demand. Learning occurs as the firm monitors the market's response to its decisions and then updates its characterization of the demand function. Of primary interest is the effect of censored data since a firm's observations often are restricted to sales. We find that the first‐period optimal selling price increases with the length of the problem horizon. However, for a given problem horizon, prices can rise or fall over time, depending on how the scale parameter influences demand. Further results include the characterization of the optimal stocking quantity decision and a computationally viable algorithm. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 303–325, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10013     

A decomposition procedure for convex quadratic programs

This article deals with the solution of convex quadratic programs by iteratively solving a master problem and a subproblem as proposed previously by Sacher. The approach has the advantage that the subproblems are linear programs so that advantage can be taken of existing schemes for solving large linear problems. At each step in solving the master problem, a closed-form solution can be specified so that the procedure is well suited for solving large quadratic programs and can take advantage of the constraint structure.     

Production lot sizing under setup and worker learning

Previous lot-sizing models incorporating learning effects focus exclusively on worker learning. We extend these models to include the presence of setup learning, which occurs when setup costs exhibit a learning curve effect as a function of the number of lots produced. The joint worker/setup learning problem can be solved to optimality by dynamic programming. Computational experience indicates, however, that solution times are sensitive to certain problem parameters, such as the planning horizon and/or the presence of a lower bound on worker learning. We define a two-phase EOQ-based heuristic for the problem when total transmission of worker learning occurs. Numerical results show that the heuristic consistently generates solutions well within 1% of optimality.