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Aerodynamic optimization of internal and external flows using the adjoint-equation method.

机译:使用伴随方程法对内部和外部流动进行空气动力学优化。

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Aerodynamic shape optimization for internal and external flows is studied. A cost function is defined based on the design objective of a particular application. Gradient-based method is used to minimize the cost function, and the adjoint equation method is applied to obtain the gradient information. Both inviscid and viscous design cases are considered, and the adjoint equations and boundary conditions are derived for the Euler equations and the Navier-Stokes equations for cases in which the cost function can be expressed as a sum of boundary integrals. The finite-volume method with time marching iterations is applied to obtain the numerical solutions of the flow governing equations and the adjoint equations. Most of the numerical methods for the flow solver are applicable to the adjoint-equation solver.; The gradient information is obtained by perturbing the geometry and calculating the corresponding cost-function variation. Only one solution of the flow field and one solution of the adjoint equations are needed to determine the gradient of the cost function, and the computational cost is essentially independent of the number of design parameters. Compared to the finite-difference method, the adjoint-equation method is much more efficient when the number of design parameters is large.; Several design cases are tested in this study, including wing design, turbomachinery blade design, and intake diffuser design. For the wing design cases, inverse design and drag minimization are tested; for the turbomachinery blade design cases, inverse design, entropy production minimization, and exit flow angle distribution control are tested; for the intake diffuser design case, non-axial momentum minimization is tested. The results show that the cost-function values are reduced significantly after the design process, which means the design method is able to improve the aerodynamic performances effectively for these design cases.
机译:研究了内部和外部流动的空气动力学形状优化。基于特定应用程序的设计目标定义成本函数。基于梯度的方法用于最小化代价函数,并采用伴随方程法获得梯度信息。考虑了无粘性和粘性设计情况,对于其中成本函数可以表示为边界积分之和的情况,针对欧拉方程和Navier-Stokes方程推导了伴随方程和边界条件。采用时间步长迭代的有限体积方法,得到了流量控制方程和伴随方程的数值解。流动解算器的大多数数值方法都适用于伴随方程解算器。通过扰动几何形状并计算相应的成本函数变化来获得梯度信息。确定成本函数的梯度仅需要流场的一种解决方案和伴随方程式的一种解决方案,并且计算成本实质上与设计参数的数量无关。与有限差分法相比,当设计参数数量较大时,伴随方程法效率更高。在这项研究中测试了几个设计案例,包括机翼设计,涡轮机械叶片设计和进气扩散器设计。对于机翼设计案例,测试了逆向设计和阻力最小化;对于涡轮机械叶片设计案例,对逆设计,熵产生最小化和出口流角分布控制进行了测试;对于进气扩散器设计案例,测试了非轴向动量最小化。结果表明,在设计过程之后,成本函数值显着降低,这意味着该设计方法能够针对这些设计案例有效地改善空气动力学性能。

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