海军推进结构的拓扑生成

Florian Dugast, St ́ephane B ́enac, Pierre Marty, Pascal Chess ́e
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引用次数: 0

摘要

以可承受的成本减少航运排放至关重要,可通过推进结构优化来实现。部件的多种选择和需要满足的约束条件(所需速度、燃料消耗、维护......)使结构设计变得越来越复杂。一些优化方法已经得到应用,例如优化柴油发电机(数量、类型和负载)以降低油耗。通过在超级配置中增加或减少某些部件的存在,已经对更复杂的结构进行了研究,但最终配置的数量仍然有限。在这项研究中,船舶结构不是预先确定的,而是由与约束条件和规则相关的组件列表生成的,从而使结构创建更加灵活。为此编写的算法遵循混合动力汽车设计中的原则,但针对海军应用调整了规则和组件。本文的主要目的是详细解释拓扑生成架构算法,而不是为特定舰船寻找最佳架构。从这一角度出发,本文介绍的测试案例具有通用性,以证明该算法可应用于各种系统配置。根据输入和输出能量类型将各组件连接在一起,并生成符合推进和酒店负载要求的架构。然后,添加物理约束条件,以建立现实的设计,如避免多余的虚假连接或定义每个组件的最大出现次数。所有的约束条件和生成算法都是用 Prolog 编写的。本文介绍了两个数值应用,其中的组件列表涵盖了不同类型的推进装置(机械和/或使用燃气轮机和/或柴油发动机的电力推进装置)以及酒店负载或加热要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topology Generation of Naval Propulsion Architecture
Reducing shipping emissions at an affordable cost is critical and can be achieved through propulsion architecture optimization. The multiple choices of components and constraints to be fulfilled (required speed, fuel consumption, maintenance, ...) make architecture design increasingly complex. Some optimization methods have already been used, for example, to optimize diesel generators (number, type and load) for fuel consumption reduction. More complex architectures have been studied by including the absence or presence of some components in a superconfiguration but in the end the number of configurations remains limited. In this study, the ship architecture is not predetermined but is generated by a list of components associated with constraints and rules, making architecture creation more flexible. The algorithm written for this purpose follows the principles found in hybrid vehicle design but with adapted rules and components for naval applications. The main objective of this paper is to explain in detail the topology generation architecture algorithm rather than to find an optimal architecture for a specific ship. From this perspective, the test cases presented are general to demonstrate that the algorithm can be applied to various system configurations. The components are linked together based on their input and output energy type and the architecture is generated to comply with propulsion and hotel load requirements. Next, physical constraints are added to build realistic designs such as avoiding spurious redundant connections or defining the maximal occurrence for each component. All the constraints and the generation algorithm are written in Prolog. Two numerical applications are presented where the list of components covers different types of propulsion (mechanical and/or electrical with gas turbines and/or diesel engines) along with hotel load or heating requirements.
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