基于遗传算法的高压涡轮喷嘴导叶双壁喷射冷却系统优化设计

IF 1.3 Q2 ENGINEERING, AEROSPACE International Journal of Turbomachinery, Propulsion and Power Pub Date : 2024-02-02 DOI:10.3390/ijtpp9010006
Michael van de Noort, Peter T. Ireland
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引用次数: 0

摘要

与传统冷却技术相比,双壁喷流冷却方案为航空发动机设计人员提供了在高压涡轮叶片中实现高总体冷却效果和对流冷却效率的机会,同时减少了冷却剂用量。这是通过将撞击、针鳍和喷流冷却结合起来实现的。优化这些冷却方案对于确保在高热流区域实现充分冷却而在低热流区域不过度使用冷却剂至关重要。由于这些系统中采用的设计变量较多,通过使用计算流体动力学(CFD)模拟进行优化是一个计算成本高且耗时的过程。本研究使用了之前开发、验证和展示的低阶流网模型(LOM),该模型可快速评估双壁喷射冷却方案中的压力、温度、质量流和热流分布。通过使用进化遗传算法(GA)优化过程,LOM 生成的结果可用于快速生成理想的冷却系统设计。其目标是在保持叶片外表面可接受的金属冷却效果的同时,最大限度地减少冷却剂的质量流量,并确保所有薄膜孔的回流边际值都高于选定的阈值。为了进行比较,还使用 ANSYS Workbench 中的 CFD 仿真进行了基于遗传聚合模型的优化。对减少冷却剂质量流量和总优化运行时间的结果与 LOM 的结果进行了分析,证明了快速低阶求解技术的优势。
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Genetic Algorithm-Based Optimisation of a Double-Wall Effusion Cooling System for a High-Pressure Turbine Nozzle Guide Vane
Double-Wall Effusion Cooling schemes present an opportunity for aeroengine designers to achieve high overall cooling effectiveness and convective cooling efficiency in High-Pressure Turbine blades with reduced coolant usage compared to conventional cooling technologies. This is accomplished by combining impingement, pin-fin and effusion cooling. Optimising these cooling schemes is crucial to ensuring that cooling is achieved sufficiently at high-heat-flux regions and not overused at low-heat-flux ones. Due to the high number of design variables employed in these systems, optimisation through the use of Computational Fluid Dynamics (CFD) simulations can be a computationally costly and time-consuming process. This study makes use of a Low-Order Flow Network Model (LOM), developed, validated and presented previously, which quickly assesses the pressure, temperature, mass flow and heat flow distributions through a Double-Wall Effusion Cooling scheme. Results generated by the LOM are used to rapidly produce an ideal cooling system design through the use of an Evolutionary Genetic Algorithm (GA) optimisation process. The objective is to minimise the coolant mass flow whilst maintaining acceptable metal cooling effectiveness around the external surface of the blade and ensuring that the Backflow Margin for all film holes is above a selected threshold. For comparison, a Genetic Aggregation model-based optimisation using CFD simulations in ANSYS Workbench is also conducted. Results for both the reduction of coolant mass flow and the total optimisation runtime are analysed alongside those from the LOM, demonstrating the benefit of rapid low-order solving techniques.
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来源期刊
CiteScore
2.30
自引率
21.40%
发文量
29
审稿时长
11 weeks
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