Aerodynamic design optimization by using a continuous adjoint method

This paper presents the fundamentals of a continuous adjoint method and the applications of this method to the aerodynamic design optimization of both external and internal flows.General formulation of the continuous adjoint equations and the corresponding boundary conditions are derived.With the adjoint method,the complete gradient information needed in the design optimization can be obtained by solving the governing flow equations and the corresponding adjoint equations only once for each cost function,regardless of the number of design parameters.An inverse design of airfoil is firstly performed to study the accuracy of the adjoint gradient and the effectiveness of the adjoint method as an inverse design method.Then the method is used to perform a series of single and multiple point design optimization problems involving the drag reduction of airfoil,wing,and wing-body configuration,and the aerodynamic performance improvement of turbine and compressor blade rows.The results demonstrate that the continuous adjoint method can efficiently and significantly improve the aerodynamic performance of the design in a shape optimization problem.     

A new method for inverse electromagnetic casting problems based on the topological derivative

The inverse electromagnetic casting problem consists in looking for a suitable set of electric wires such that the electromagnetic field induced by an alternating current passing through them makes a given mass of liquid metal acquire a predefined shape. In this paper we propose a new method for the topology design of such inductors. The inverse electromagnetic casting problem is formulated as an optimization problem, and topological derivatives are considered in order to locate new wires in the right position. Several numerical examples are presented showing that the proposed technique is effective to design suitable inductors.     

透平叶栅三维形状反问题研究

随着CFD技术的发展,基于伴随方法的求解Euler和NS方程的气动优化设计已成为流体力学形状反问题研究中的热门领域.本文应用该方法对透平叶栅进行三维气动优化设计,详细推导了Euler方程伴随系统的偏微分方程组及其各类边界条件,首次给出了透平内流伴随方程边界条件的具体形式,并给出伴随变量的物理意义.结合拟牛顿算法发展了三维透平叶栅形状反问题气动优化算法,并给出了算法的流程.     

Adjoint sensitivity computations for an embedded-boundary Cartesian mesh method

We present a new approach for the computation of shape sensitivities using the discrete adjoint and flow-sensitivity methods on Cartesian meshes with general polyhedral cells (cut-cells) at the wall boundaries. By directly linearizing geometric constructors of the cut-cells, an efficient and robust computation of shape sensitivities is achieved for problems governed by the Euler equations. The accuracy of the linearization is verified by the use of a model problem with an exact solution. Verification studies show that the convergence rate of gradients is second-order for design variables that do not alter the boundary shape, and is reduced to first-order for shape design problems. The approach is applied to several three-dimensional problems, including inverse design and shape optimization of a re-entry capsule in hypersonic flow. The results show that reliable approximations of the gradient are obtained in all cases. The approach is well-suited for geometry control via computer-aided design, and is especially effective for conceptual design studies with complex geometry where fast turn-around time is required.     

A scalable framework for the solution of stochastic inverse problems using a sparse grid collocation approach

Experimental evidence suggests that the dynamics of many physical phenomena are significantly affected by the underlying uncertainties associated with variations in properties and fluctuations in operating conditions. Recent developments in stochastic analysis have opened the possibility of realistic modeling of such systems in the presence of multiple sources of uncertainties. These advances raise the possibility of solving the corresponding stochastic inverse problem: the problem of designing/estimating the evolution of a system in the presence of multiple sources of uncertainty given limited information.A scalable, parallel methodology for stochastic inverse/design problems is developed in this article. The representation of the underlying uncertainties and the resultant stochastic dependant variables is performed using a sparse grid collocation methodology. A novel stochastic sensitivity method is introduced based on multiple solutions to deterministic sensitivity problems. The stochastic inverse/design problem is transformed to a deterministic optimization problem in a larger-dimensional space that is subsequently solved using deterministic optimization algorithms. The design framework relies entirely on deterministic direct and sensitivity analysis of the continuum systems, thereby significantly enhancing the range of applicability of the framework for the design in the presence of uncertainty of many other systems usually analyzed with legacy codes. Various illustrative examples with multiple sources of uncertainty including inverse heat conduction problems in random heterogeneous media are provided to showcase the developed framework.     

Three-dimensional elliptic solvers for interface problems and applications

Second-order accurate elliptic solvers using Cartesian grids are presented for three-dimensional interface problems in which the coefficients, the source term, the solution and its normal flux may be discontinuous across an interface. One of our methods is designed for general interface problems with variable but discontinuous coefficient. The scheme preserves the discrete maximum principle using constrained optimization techniques. An algebraic multigrid solver is applied to solve the discrete system. The second method is designed for interface problems with piecewise constant coefficient. The method is based on the fast immersed interface method and a fast 3D Poisson solver. The second method has been modified to solve Helmholtz/Poisson equations on irregular domains. An application of our method to an inverse interface problem of shape identification is also presented. In this application, the level set method is applied to find the unknown surface iteratively.     

Shape and topology optimization based on the phase field method and sensitivity analysis

This paper discusses a structural optimization method that optimizes shape and topology based on the phase field method. The proposed method has the same functional capabilities as a structural optimization method based on the level set method incorporating perimeter control functions. The advantage of the method is the simplicity of computation, since extra operations such as re-initialization of functions are not required. Structural shapes are represented by the phase field function defined in the design domain, and optimization of this function is performed by solving a time-dependent reaction diffusion equation. The artificial double well potential function used in the equation is derived from sensitivity analysis. The proposed method is applied to two-dimensional linear elastic and vibration optimization problems such as the minimum compliance problem, a compliant mechanism design problem and the eigenfrequency maximization problem. The numerical examples provided illustrate the convergence of the various objective functions and the effect that perimeter control has on the optimal configurations.     

Comparison of asynchronous particle swarm optimization and dynamic differential evolution for partially immersed conductor

The application of two techniques for the of shape reconstruction of a perfectly two-dimensional conducting cylinder from mimic measurement data is studied in the present paper. After an integral formulation, the microwave imaging is recast as a nonlinear optimization problem; a cost function is defined by the norm of a difference between the measured scattered electric fields and the calculated scattered fields for an estimated shape of a conductor. Thus, the shape of conductor can be obtained by minimizing the cost function. In order to solve this inverse scattering problem, transverse electric (TE) waves are incident upon the objects and two techniques are employed to solve these problems. The first is based on an asynchronous particle swarm optimization (APSO) and the second is a dynamic differential evolution (DDE). Both techniques have been tested in the case of simulated mimic measurement data contaminated by additive white Gaussian noise. Numerical results indicate that the DDE algorithm and the APSO have almost the same reconstructed accuracy.     

The shape gradient of the least-squares objective functional in optimal shape design problems of radiative heat transfer

Optimal shape design problems of steady-state radiative heat transfer are considered. The optimal shape design problem (in the three-dimensional space) is formulated as an inverse one, i.e., in the form of an operator equation of the first kind with respect to a surface to be optimized. The operator equation is reduced to a minimization problem via a least-squares objective functional. The minimization problem has to be solved numerically. Gradient minimization methods need the gradient of a functional to be minimized. In this paper the shape gradient of the least-squares objective functional is derived with the help of the shape sensitivity analysis and adjoint problem method. In practice a surface to be optimized may be (or, most likely, is to be) given in a parametric form by a finite number of parameters. In this case the objective functional is, in fact, a function in a finite-dimensional space and the shape gradient becomes an ordinary gradient. The gradient of the objective functional, in the case that the surface to be optimized is given in a finite-parametric form, is derived from the shape gradient. A particular case, that a surface to be optimized is a “two-dimensional” polyhedral one, is considered. The technique, developed in the paper, is applied to a synthetic problem of designing a “two-dimensional” radiant enclosure.     

Optimal brushless DC motor design using genetic algorithms

This paper presents a method for the optimal design of a slotless permanent magnet brushless DC (BLDC) motor with surface mounted magnets using a genetic algorithm. Characteristics of the motor are expressed as functions of motor geometries. The objective function is a combination of losses, volume and cost to be minimized simultaneously. Electrical and mechanical requirements (i.e. voltage, torque and speed) and other limitations (e.g. upper and lower limits of the motor geometries) are cast into constraints of the optimization problem. One sample case is used to illustrate the design and optimization technique.     

Shape optimization towards stability in constrained hydrodynamic systems

Hydrodynamic stability plays a crucial role for many applications. Existing approaches focus on the dependence of the stability properties on control parameters such as the Reynolds or the Rayleigh number. In this paper we propose a numerical method which aims at solving shape optimization problems in the context of hydrodynamic stability. The considered approach allows to guarantee hydrodynamic stability by modifying parts of the underlying geometry within a certain flow regime. This leads to a formulation of a shape optimization problem with constraints on the eigenvalues related to the linearized Navier–Stokes equations. In that context the eigenvalue problem is generally non-symmetric and may involve complex eigenvalues. To validate the proposed numerical approach we consider the flow around a body in a channel. The shape of the body is parameterized and can be changed by means of a discrete number of design variables. It is our aim to find a design which minimizes the drag force and ensures at the same time hydrodynamic stability while keeping the volume of the body constant. The numerical results show that a transition from an unstable design to a stable one is attainable by considering an adequate change of the body shape. The resulting bodies are long and flat which corresponds to common intuition.     

Upper bound of errors in solving the inverse problem of identifying a voice source

The paper considers the inverse problem of finding the shape of a voice-source pulse from a specified segment of a speech signal using a special mathematical model that relates these quantities. A variational method for solving the formulated inverse problem for two new parametric classes of sources is proposed: a piecewise-linear source and an A-source. The error in the obtained approximate solutions of the inverse problem is considered, and a technique to numerically estimate this error is proposed, which is based on the theory of a posteriori estimates of the accuracy in solving ill-posed problems. A computer study of the adequacy of the proposed models of sources, and a study of the a posteriori estimates of the accuracy in solving inverse problems for such sources were performed using various types of voice signals. Numerical experiments for speech signals showed satisfactory properties of such a posteriori estimates, which represent the upper bounds of possible errors in solving the inverse problem. The estimate of the most probable error in determining the source-pulse shapes for the investigated speech material is on average ~7%. It is noted that the a posteriori accuracy estimates can be used as a criterion for the quality of determining the voice-source pulse shape in the speaker-identification problem.     

小阻尼封闭空间声压级灵敏度分析与优化设计

本文研究了小阻尼界面封闭空间低频声学有限元分析、灵敏度分析和优化设计问题。分别用模态法和直接法计算了封闭空间内声压级响应，并推导了声压级响应对声空间边界形状控制参数的灵敏度分析公式，在此基础上建立了小阻尼空间声学问题的优化模型，同时给出了优化求解算法，并在JIFEX软件中进行了程序实现。本文提出的灵敏度分析和优化设计方法可以使声场的边界布局更为合理，从而达到改进小阻尼界面封闭空间声学性能的目的。数值算例验证了本文提出的灵敏度分析和优化算法的有效性。     

The Adjoint Method for an Inverse Design Problem in the Directional Solidification of Binary Alloys

This paper presents a systematic procedure based on the adjoint method for solving a class of inverse directional alloy solidification design problems in which a desired growth velocityv_fis achieved under stable growth conditions. To the best of our knowledge, this is the first time that a continuum adjoint formulation is proposed for the solution of an inverse problem with simultaneous heat and mass transfer, thermo-solutal convection, and phase change. In this paper, the interfacial stability is considered to imply a sharp solid–liquid freezing interface. This condition is enforced using the constitutional undercooling criterion in the form of an inequality constraint between the thermal and solute concentration gradients,GandG_c, respectively, at the freezing front. The main unknowns of the design problem are the heating and/or cooling boundary conditions on the mold walls. The inverse design problem is formulated as a functional optimization problem. The cost functional is defined by the square of theL₂norm of the deviation of the freezing interface temperature from the temperature corresponding to thermodynamic equilibrium. A continuum adjoint system is derived to calculate the adjoint temperature, concentration, and velocity fields such that the gradient of the cost functional can be expressed analytically. The cost functional minimization process is realized by the conjugate gradient method via the finite element method solutions of the continuum direct, sensitivity, and adjoint problems. The developed formulation is demonstrated with an example of designing the directional solidification of a binary aqueous solution in a rectangular mold such that a stable vertical interface advances from left to right with a desired growth velocity.     

光参量啁啾脉冲放大的逆问题

针对光参量啁啾脉冲放大的逆问题,即如何在给定输出信号光脉冲波形的前提下,通过计算得到输入信号光脉冲波形,提出了相应的计算模型和方法.以分步傅里叶变换和四阶龙格-库塔法为基础,通过数值拟合等方法,建立了输入-输出信号光强之间的定量关系.分别以预期输出信号光脉冲为啁啾高斯脉冲以及具有特定形状的整形脉冲为例,通过逆算得到了相应的输入信号光脉冲波形.研究结果表明,该逆算方法具有原理简单、计算快速准确等优点,可为激光脉冲整形设计提供参考. 关键词： 光参量啁啾脉冲放大 逆问题 啁啾脉冲 脉冲整形     

阻抗障碍物声散射的反问题

研究了从声散射场的远场分布的信息来再现声阻抗障碍物形状的反问题,建立了求解这类反问题的一种非线性最优化模型,并提出了数值实现该非线性最优化模型的一种两步调整迭代算法.两步过程的应用使在确定未知障碍物形状的非线性最优化步中未知函数的个数达到了最少,而在调整迭代过程中,通过利用前一迭代步所得重构信息,使重构精度得到了相当大的改进.所建立的反演算法的一个特别吸引人的性质是,只需要远场分布的一个Fourier系数即可对未知声阻抗障碍物作几何物形的设别.对大量具有各种几何形状的二维障碍物的数值算例保证了本算法是实用和有效的.     

使用类别形状函数的多目标气动外形优化设计

在飞行器的气动外形优化设计中, 参数化方法和优化算法具有十分重要的作用, 对优化的计算时间设计空间的数学特性有着深刻的影响.类别形状函数(class and shape transformation, CST)方法是一种简洁高效的参数化方法, 但对于复杂曲面很难使用统一的CST方法进行拟合.文章首先介绍了CST方法的三维实现, 分析了其数学性质, 提出了分块CST参数化方法, 保留CST方法的特性, 实现了分块曲面之间的光滑连接.针对气动外形优化设计的复杂情况, 需要根据具体的飞行任务提出设计目标, 并处理不同目标的矛盾问题.其次采用Pareto策略自动寻找最优方案集, 并基于分块CST参数化方法遗传算法和气动力快速计算方法, 对类乘波翼身组合飞行器进行了优化设计, 并改变原有问题的设定条件优化得到了全新外形.研究结果表明分块CST方法参数少, 精度高, Pareto策略处理多目标准确有效, 是气动外形优化设计中非常有用的工具.      

Shape and topology optimization of compliant mechanisms using a parameterization level set method

In this paper, a parameterization level set method is presented to simultaneously perform shape and topology optimization of compliant mechanisms. The structural shape boundary is implicitly embedded into a higher-dimensional scalar function as its zero level set, resultantly, establishing the level set model. By applying the compactly supported radial basis function with favorable smoothness and accuracy to interpolate the level set function, the temporal and spatial Hamilton–Jacobi equation from the conventional level set method is then discretized into a series of algebraic equations. Accordingly, the original shape and topology optimization is now fully transformed into a parameterization problem, namely, size optimization with the expansion coefficients of interpolants as a limited number of design variables.Design of compliant mechanisms is mathematically formulated as a general optimization problem with a nonconvex objective function and two additionally specified constraints. The structural shape boundary is then advanced as a process of renewing the level set function by iteratively finding the expansion coefficients of the size optimization with a sequential convex programming method. It is highlighted that the present method can not only inherit the merits of the implicit boundary representation, but also avoid some unfavorable features of the conventional discrete level set method, such as the CFL condition restriction, the re-initialization procedure and the velocity extension algorithm. Finally, an extensively investigated example is presented to demonstrate the benefits and advantages of the present method, especially, its capability of creating new holes inside the design domain.     

抛物型方程的演化参数识别方法

给出了一种利用演化计算方法求解微分方程中的参数识别类型反问题的方法。该方法把参数识别问题转化为泛函的优化问题用演化算法来求解,指定待定参数的函数类形式,用遗传算法(Genetic Algorithms)来演化待求参数的最优估计值,并将该方法运用于线性扩散方程和拟线性对流扩散反方程反问题的数值模拟中。     

动静叶栅优化改型及其性能分析

本文对动静叶栅分别进行优化改型,并对改型前后叶栅的气动性能进行数值分析。动静叶栅的优化改型基于正反问题相结合的流函数方法,性能分析一方面基于单排叶栅定常粘性流动的数值计算,另一方面基于动静叶栅相互干扰非定常粘性流动的数值计算。算例结果表明,经过优化改型后的动静叶栅的气动性能,无论在定常流动条件下还是在非定常流动条件下,相比改型前均有较大幅度的改善。