硕士论文代写：有关压气机技术的优化与设计探究
目录：
摘要 3-4
Abstract 4-5
第1章绪论 8-19
1.1引言 8-10
1.2压气机发展与设计 10-17
1.2.1压气机发展概况和趋势 10-11
1.2.2压气机技术的发展 11-12
1.2.3压气机设计思想的发展 12-17
1.3本文的主要工作 17-19
第2章压气机设计体系及优化设计 19-28
2.1设计体系的发展 19-26
2.1.1一维气动设计 19-20
2.1.2准三维设计 20-22
2.1.3全三维粘性流数值预测设计 22-26
2.2压气机优化设计在国内外的研究现状 26-27
2.3小结 27-28
第3章轴流压气机一维优化设计平台的建立与应用 28-42
3.1引言 28-36
3.1.1iSIGHT简介 28-30
3.1.2遗传算法的基本原理及特点 30-33
3.1.3多目标遗传算法的基本概念和主要方法 33-34
3.1.4NSGA-II介绍 34-36
3.2轴流压气机一维气动优化设计平台的建立 36-39
3.2.1简要分析 36
3.2.2iSIGHT集成 36-39
3.3一维多目标优化的模型 39
3.4单级轴流压气机气动优化设计 39-40
3.5四级轴流压气机气动优化设计 40-41
3.6小结 41-42
第4章轴流压气机准三维气动优化平台的建立 42-51
4.1准三维设计分析方法 42-46
4.1.1简介 42-43
4.1.2流线曲率法解S2流面问题 43-44
4.1.3求解步骤 44-46
4.2轴流压气机准三维气动优化平台的建立 46-49
4.2.1简述 46-47
4.2.2iSIGHT集成 47-49
4.3算例(单级风扇)的优化结果及分析 49-50
4.4本章小结 50-51
第5章三维跨音速压气机叶栅优化设计及分析 51-75
5.1引言 51-52
5.2三维叶轮机械叶栅气动优化设计流程 52-60
5.2.1叶片参数化造型方法 52-54
5.2.2数值优化方法及过程 54-60
5.3优化前性能计算 60-63
5.4目标函数 63-64
5.5优化变量及约束条件 64-66
5.5.1积叠规律优化 64-65
5.5.2叶型优化 65-66
5.6优化结果及分析 66-74
5.6.1积叠规律优化 66-69
5.6.2叶型优化 69-74
5.7本章小结 74-75
结论 75-76
参考文献 76-81
致谢 81
【摘要】 气动优化设计技术是叶轮机械设计中的一个重要的研究方向,风扇/压气机气动优化设计技术,在推动高性能航空轴流压气机的发展上具有重要的作用。随着计算流体力学和现代优化计算方法的飞速发展,叶轮机械的优化设计技术得到了快速发展。但是叶轮机械,尤其是跨音速轴流压气机叶片的气动优化设计仍然是一个具有挑战性的研究领域。本论文应用iSIGHT优化平台进行了轴流压气机一维、准三维气动优化设计,同时基于商业软件NUMECA的叶轮机械全三维优化设计平台Design3D,以已有跨音速轴流压气机转子叶片为参考叶片,对其进行了三维叶片优化设计研究,主要开展了以下几个方面的工作:首先,本文研究了轴流压气机的一维、准三维气动设计计算方法,将压气机计算程序和iSIGHT集成,建立了压气机优化平台。针对压气机设计的特点,采用基于快速非劣解排序和精英策略的多目标遗传算法(NSGA-II)作为压气机设计的优化方法,以总绝热效率最大化为目标函数,将其应用于轴流压气机的一维、准三维的优化设计中。其次,采用Numeca的FINE/Turbo计算软件对原始叶型进行了三维数值模拟。计算结果表明,计算软件Fine/Turbo能很好的预测跨音速轴流压气机的总性能及内部流场结构,保证了计算的可靠性。由此可以看出在此基础上进行优化设计是可行的,并为以后的优化设计工作奠定了基础。通过将六个不同叶展处(叶根、10%叶展、32%叶展、61%叶展、85%叶展和叶尖)的叶型进行径向积叠生成三维叶片来参数化参考叶片。中弧线定义为3次B样条曲线。压力面和吸力面都是关于中弧线的高阶Bezier曲线。这为后续优化设计工作提供了优化设计变量。最后,采用三维N-S方程流场计算、网格自动生成、三维叶片参数化造型与人工神经网络和遗传算法寻优相结合的方法,以总绝热效率最大为目标函数,对参考叶片进行了周向积叠规律和三维叶片型线优化设计。优化设计结果表明,优化叶片的气动性能较参考叶片明显提高,可以达到控制激波的强度和位置的目的,削弱了流动分离,减少了流动损失,使叶轮整体性能都得到了提高。表明本文的气动优化设计方法,是获得低损失高效率性能的叶片的有效途径。
硕士论文代写【Abstract】 Aerodynamic optimization design technology is an important research direction in turbomachinery design. Aerodynamic optimization technology for compressor design plays an important role in the development of high performance axial flow compressor. With the rapid development of computational fluid dynamics and optimization algorithm, the optimization techniques of turbomachinery have been developed speedly. But the aerodynamic optimization of the turbomachinery blade, especially the transonic compressor blade, is still a challenge area. In this paper, the optimization platform of the iSIGHT is used in one dimensional and quasi-three dimensional aerodynamic optimization design of axial flow compressor.At the same time, optimization design of the transonic compressor, is carried out for the minimization of the total energy loss coefficient, based on the software of Design3D-a presentation of the Numeca optimization enviroment of turbomachinery blades. These studies mainly consist of the following aspects:First, one dimension and quasi-three dimensional design method of multistage axial flow compressor was studied. Thanks to a combination of the Compressor program and the iSIGHT optimization enviroment, a compressor optimization platform has been established and is carried out for the minimization of the total energy loss coefficient in one dimension and quasi-three dimensional designs. Point to the character of compressor optimization design, axial flow compressor optimization method adopt as a fast elitist non-dominated sorting genetic algorithm (NSGA-11).Second, the detailed numerical simulation on the original blade profiles is done. The numerical results which ensure the computational reliability and establishe the base on following aerodynamic optimization work. the parameterized blade is obtained by stacking four blade sections along the span(hub, 10%span, 32%span,61%span, 85%span and tip), with the help of Autoblade,each blade section can be defined by the suction side and pressure side mode. Both suction and pressure sides are constructed in the form of a high degree Bezier Curve with respect to the camber line. And the camber line is parameterized by a three-order B-Spline. This will also provide variables for the following optimizationThird, the optimization design of a three dimensional blade profile was carried out for the reference transonic compressor. And it is based on the method that consists of three dimensiona Navier-Stokes flow computation, mesh generated automatically, three dimensional blade section parameterization and genetic algorithm integrated with artificial neural network. The optimization objective is minmum the total energy loss coefficient. Compared with the reference blade, the aerodynamic preformences of the optimized blade is improved obviously. The results show that this optimization method can control the intensity and the position of the inlet shockwave, weaken the flow separation, reduce the flow losses, and that the present method is the efficient way to get the compressor blade with the low flow losses and high eficiency.
【关键词】 轴流压气机叶片； 遗传算法； 人工神经网络； 优化平台； 气动优化设计；
硕士论文代写【Key words】 Axial Compressor Blad； Genetic Algorithm； Artificial Neural Network； Optimization Platform； Aerodynamic Optimization Design；