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A Generalized Multi-Commodity Network Flow Model for Space Exploration Logistics

机译:航天探索物流的通用多商品网络流模型

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In transition to a new era of human space exploration, the question is what the next-generation space logistics paradigm should be. The past studies on space logistics have been mainly focused on a "vehicle" perspective such as propulsive feasibility, cargo capacity constraints, and manifesting strategies, with the arbitrarily predetermined logistics network. But how do we select an optimal logistics network? Especially if we can utilize in-situ resources on the Moon and Mars, it will add complexity to network selection problem. The objective of this paper is to develop a comprehensive graph-theoretic modeling framework to quantitatively evaluate and optimize space exploration logistics from a "network" perspective. In an attempt to create such a modeling framework, we develop a novel network flow model referred to as the generalized multi-commodity network flow (GMCNF) model. On top of the classical network flow problems, the GMCNF model proposed in this paper introduces three types of matrix multiplications (requirement, transformation, and concurrency), and also allows loop edges associated with nodes (graph loops) and multiple edges between the same end nodes (multigraph). With this modification, the model can handle multiple commodities that interact with each other in the form of requirement at nodes, transformation on edges, and concurrency within edges. A linear programming (LP) formulation of the GMCNF model is applied to human exploration of Mars. First we solve the baseline problem with a demand that is equivalent to that of the NASA's Mars Design Reference Architecture (DRA) 5.0 scenario. It is found that the solution saves 67.5% from the Mars DRA 5.0 reference scenario in terms of the initial mass in low-Earth orbit (IMLEO) primarily because chemical (LOX/LH2) propulsion is used along with oxygen-rich ISRU. We also present one possible scenario with two "gateway" resource depots at GTO and DTO with orbital transfer vehicles (OTVs) running in the cislunar and Martian systems. Then we solve variant problems that have different settings to see the effect of each factor. Findings include: taking advantage of oxygen-rich ISRU, LOX/LH_2 is preferred to nuclear thermal rocket (NTR), the aerobraking option as well as ISRU availability on the Moon make great contributions in reducing the total mass to be launched from Earth, and as the ISRU production rate decreases, ISRU in each location becomes worthless at a certain threshold and the network topology changes toward direct paths using NTR.
机译:在向人类太空探索的新时代过渡时,问题在于下一代太空物流范式应该是什么。过去有关空间物流的研究主要集中在“车辆”角度,例如推进可行性,货物容量限制和显示策略,以及任意预定的物流网络。但是,我们如何选择最佳的物流网络?特别是如果我们可以利用月球和火星上的原地资源,将会增加网络选择问题的复杂性。本文的目的是开发一个全面的图论建模框架,以从“网络”的角度定量评估和优化太空探索物流。为了创建这样的建模框架,我们开发了一种新颖的网络流模型,称为广义多商品网络流(GMCNF)模型。除了经典的网络流量问题外,本文提出的GMCNF模型还介绍了三种类型的矩阵乘法(需求,变换和并发),还允许与节点关联的循环边(图循环)和同一端之间的多个边节点(多图)。通过这种修改,模型可以处理多种商品,这些商品以节点需求,边转换和边内并发的形式相互交互。 GMCNF模型的线性规划(LP)公式适用于人类对火星的探索。首先,我们以与NASA的“火星设计参考体系结构(DRA)5.0”方案相同的需求来解决基线问题。结果发现,就低地球轨道(IMLEO)的初始质量而言,该解决方案比Mars DRA 5.0参考方案节省了67.5%,这主要是因为化学(LOX / LH2)推进与富氧ISRU一起使用。我们还提出了一种可能的情况,即在GTO和DTO的两个“网关”资源仓库中,运行着在月球和火星系统中运行的轨道转移车(OTV)。然后,我们解决具有不同设置的变量问题,以查看每个因素的影响。研究结果包括:利用富含氧气的ISRU,LOX / LH_2比核热火箭(NTR)更受青睐,航空制动选项以及ISRU在月球上的可用性为减少从地球发射的总质量做出了巨大贡献,并且随着ISRU生产率的降低,每个位置的ISRU在某个阈值处变得一文不值,并且网络拓扑使用NTR向直接路径更改。

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