基于网格变形技术的跨声速压气机叶片伴随优化方法研究

Adjoint Optimization Method for Transonic Compressor Blade Based on Mesh Deformation Technique

关键词:  Rotor 37  伴随法  动网格  优化  效率  熵产

Key words:  Rotor 37  Adjoint method  Dynamic mesh  Optimization  Efficiency  Entropy generation

摘要:

为研究压气机三维叶片对激波和复杂二次流动的影响机理及提升相应的控制技术，耦合伴随优化方法、网格变形技术和数值计算方法，建立了压气机叶片伴随优化设计系统，利用该系统，在98%堵塞流量工况，对Rotor 37转子的叶片进行了优化。叶片优化后，压气机等熵效率提高了0.79%，压比提升了0.48%，质量流量增加了0.71%，出口熵增降低了3.85%。此外，叶片优化可提升全工况下的效率和总压比，特别是在大逆压梯度工况，性能提升更为显著。流动机理研究表明，叶片优化后，前缘往叶背偏移，尾缘往叶盆偏移，调整了气流进口几何角和出气角沿叶高的分布，减少了气流出口参数不均匀所带来的掺混损失，优化叶片在叶片前缘形成一个弓形结构，降低了前缘马赫数峰值，使边界层更好发展；优化叶片调整了叶片最大弯度位置，使气流折转更合理。叶片优化使得叶片中部负荷前移，激波位置延后，减少了激波和边界层之间的干扰，从而改善了激波后的流动。此外，叶片优化也降低了叶片后部的负荷，进一步改善了叶片后部的流动状况。上述结果证明了基于伴随优化方法开展压气机叶片优化的可行性和有效性。

Abstract:

In order to study the influence mechanism of three-dimensional compressor blades on shock waves and complex secondary flow and improve the corresponding control technology， an adjoint optimization platform is established for a compressor blade， by coupling adjoint optimization method， mesh deformation technique and numerical simulation technique. To improve the compressor isentropic efficiency， the blade of Rotor 37 is optimized at 98% choking mass flow rate. After the blade optimization， the compressor isentropic efficiency rises by 0.79%， the total pressure ratio grows by 0.48%， the mass flow increases by 0.71%， and the outlet entropy generation drops by 3.85%. More importantly， the blade optimization can improve the efficiency and total pressure ratio at nearly all working conditions， in particular， the performance improvement is more significant at larger inverse-pressure-gradient conditions. The flow mechanism shows that after the blade is optimized， the leading edge of the blade is offset to the back of the blade， and the trailing edge is offset to the leaf pot， the distribution of the air inlet and outlet angle along the height of the blade is adjusted to reduce the mixing loss caused by uneven outlet air flow. A bow-shaped structure is formed at the leading edge of the blade， which reduces the peak Mach number of the leading edge and makes the boundary layer better develop， the position of the maximum blade curvature is adjusted to make the airflow turn more reasonably. Besides， after blade optimization， the load on the middle of the blade moves forward， and the shock wave is delayed， which reduces the interference between the shock wave and the boundary layer so that the airflow after shock waves is improved. In addition， the blade optimization also reduces the load on the rear of the blade， which further results in better flow characteristics. The above results demonstrate the feasibility and effectiveness of the adjoint optimization method for compressor blade optimization.