当前位置: X-MOL 学术Numer. Heat Transf. Part A Appl. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Multi-optimization of a specific laminated cooling structure for overall cooling effectiveness and pressure drop
Numerical Heat Transfer, Part A: Applications ( IF 2 ) Pub Date : 2020-10-28 , DOI: 10.1080/10407782.2020.1835105
Chen Wang 1 , Jingzhou Zhang 1 , Chunhua Wang 1 , Xiaoming Tan 1
Affiliation  

Abstract The structural optimization of a specific laminated cooling structure is conducted under gas turbine combustor representative aero-thermal conditions, with the aim at improving its overall cooling effectiveness. The optimization procedure is realized by using conjugate heat transfer CFD analysis and radial basis function neural network (RBFNN) surrogated model. For this specific laminated cooling structure, both the thickness of impinging plate (ti) and the thickness of film cooling plate (tf) are all fixed as 0.5 mm. The other geometric parameters including impinging-hole diameter(di), pin-fin diameter(dp), film-hole diameter (df), inner height of double walls (H), streamwise hole-to-hole pitch (S) and spanwise hole-to-hole pitch (P) are selected as the design variables. Two geometric constrains are considered that the total thickness of laminated cooling structure is not bigger than 2 mm, and the minimum clearance between adjacent fins should be bigger than 0.5 mm. By using the current CFD-based optimization methodology, the optimized laminated cooling structures are presented from the given range of possible geometric variables. An optimized laminated cooling structures makes the maximum spatially-averaged overall cooling effectiveness approach to 0.9, and the other for minimum relative total pressure drop can reach 0.17%. Moreover, it is found that the thermal stress has a regularity with the overall cooling effectiveness.

中文翻译:

针对整体冷却效率和压降的特定叠层冷却结构的多重优化

摘要 在具有代表性的燃气轮机燃烧室气热工况下,对特定叠层冷却结构进行结构优化,以提高其整体冷却效果。优化程序是通过使用共轭传热 CFD 分析和径向基函数神经网络 (RBFNN) 代理模型来实现的。对于这种特定的叠层冷却结构,冲击板的厚度(ti)和薄膜冷却板的厚度(tf)均固定为 0.5 mm。其他几何参数包括冲击孔直径(di)、针翅直径(dp)、膜孔直径(df)、双壁内高(H)、流向孔距(S)和展向孔间距 (P) 被选为设计变量。考虑两个几何约束,即叠片散热结构的总厚度不大于2 mm,相邻翅片之间的最小间隙应大于0.5 mm。通过使用当前基于 CFD 的优化方法,可以从给定的可能几何变量范围内呈现优化的叠层冷却结构。优化的叠层冷却结构使最大空间平均整体冷却效率接近 0.9,另一种最小相对总压降可达 0.17%。此外,发现热应力与整体冷却效果具有规律性。优化的叠层冷却结构是从给定的可能几何变量范围内呈现的。优化的叠层冷却结构使最大空间平均整体冷却效率接近 0.9,另一种最小相对总压降可达 0.17%。此外,发现热应力与整体冷却效果具有规律性。优化的叠层冷却结构是从给定的可能几何变量范围内呈现的。优化的叠层冷却结构使最大空间平均整体冷却效率接近 0.9,另一种最小相对总压降可达 0.17%。此外,发现热应力与整体冷却效果具有规律性。
更新日期:2020-10-28
down
wechat
bug