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Modeling aerial refueling operations.

机译:模拟空中加油作业。

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摘要

Aerial Refueling (AR) is the act of offloading fuel from one aircraft (the tanker) to another aircraft (the receiver) in mid flight. Meetings between tanker and receiver aircraft are referred to as AR events and are scheduled to: escort one or more receivers across a large body of water; refuel one or more receivers; or train receiver pilots, tanker pilots, and boom operators. In order to efficiently execute the Aerial Refueling Mission, the Air Mobility Command (AMC) of the United States Air Force (USAF) depends on computer models to help it make tanker basing decisions, plan tanker sorties, schedule aircraft, develop new organizational doctrines, and influence policy. We have worked on three projects that have helped AMC improve its modeling and decision making capabilities.;Optimal Flight Planning. Currently Air Mobility simulation and optimization software packages depend on algorithms which iterate over three dimensional fuel flow tables to compute aircraft fuel consumption under changing flight conditions. When a high degree of fidelity is required, these algorithms use a large amount of memory and CPU time. We have modeled the rate of aircraft fuel consumption with respect to AC GrossWeight, Altitude and Airspeed. When implemented, this formula will decrease the amount of memory and CPU time needed to compute sortie fuel costs and cargo capacity values. We have also shown how this formula can be used in optimal control problems to find minimum costs flight plans.;Tanker Basing Demand Mismatch Index. Since 1992, AMC has relied on a Tanker Basing/AR Demand Mismatch Index which aggregates tanker capacity and AR demand data into six regions. This index was criticized because there were large gradients along regional boundaries. Meanwhile tankers frequently cross regional boundaries to satisfy the demand for AR support. In response we developed continuous functions to score locations with respect to their proximity to demand for AR support as well as their isolation from existing tanker bases.;Optimal Scheduling. Because most of the tanker resources are controlled by individual Air National Guard Units there is little to no central authority coordinating tanker and receiver training schedules. We have been able to show that significant flying hour savings could be achieved if National Guard tanker units were to yield some of their scheduling autonomy to a central authority which was charged with the responsibility of matching tanker training requirements to receiver training requirements.
机译:空中加油(AR)是在飞行中从一架飞机(油轮)向另一架飞机(接收器)卸载燃料的行为。加油机和接收器飞机之间的会议被称为AR事件,其安排为:护送一个或多个接收器跨越大片水域;给一个或多个接收器加油;或训练收油机驾驶员,油轮驾驶员和吊臂操作员。为了有效执行空中加油任务,美国空军的空中机动司令部(AMC)依靠计算机模型来帮助其做出加油机决策,计划加油机出动,安排飞机时间,制定新的组织学说,和影响政策。我们已经完成了三个项目,这些项目已经帮助AMC改善了其建模和决策能力。当前,空气流动性仿真和优化软件包依赖于算法,该算法在三维燃油流表上进行迭代以计算变化的飞行条件下的飞机燃油消耗。当需要高度保真度时,这些算法会占用大量内存和CPU时间。我们已经模拟了飞机油耗相对于AC总重,高度和空速的比率。实施后,此公式将减少计算出站燃油成本和货物容量值所需的内存和CPU时间。我们还展示了如何在最佳控制问题中使用此公式来找到最低成本的飞行计划。自1992年以来,AMC一直依靠油轮基础/ AR需求失配指数将油轮容量和AR需求数据汇总到六个区域。批评该指数是因为沿区域边界存在较大的梯度。同时,油轮经常跨越区域边界,以满足对AR支持的需求。作为响应,我们开发了连续功能,以根据与AR支持需求的接近程度以及与现有油轮基地的隔离程度来对位置进行评分。由于大多数加油机资源是由各个空军国民警卫队控制的,因此几乎没有中央机构来协调加油机和接收器的培训时间表。我们已经证明,如果国民警卫队的加油机部门将其部分调度自主权交给中央主管部门,则可以节省大量的飞行时间,中央主管部门负责将加油机培训要求与接收方培训要求相匹配。

著录项

  • 作者

    McCoy, Allen B., III.;

  • 作者单位

    Washington University in St. Louis.;

  • 授予单位 Washington University in St. Louis.;
  • 学科 Mathematics.;Engineering Aerospace.
  • 学位 D.Sc.
  • 年度 2010
  • 页码 93 p.
  • 总页数 93
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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