多体系统动力学优化设计的增广Lagrange乘子法

针对多体系统的非线性受约束动态优化设计通用模型,基于连续可微目标函数和一阶、二阶灵敏度分析给出多体系统动力学优化设计的增广Lagrange乘子法.其中基于多体系统动力学方程的一阶设计灵敏度采用伴随变量方法进行计算,二阶设计灵敏度使用混合方法进行计算,在设计变量较多时具有较高的计算效率.最后对曲柄-滑块系统数值算例使用增广Lagrange乘子方法进行约束优化,通过对使用不同方法进行一阶灵敏度分析和二阶灵敏度分析所得的最优值、迭代次数及运行时间的比较,得出一阶灵敏度分析中使用变尺度方法效率较高,而使用二阶灵敏度分析可以进一步提高优化效率.     

非粘滞阻尼系统时程响应分析的精细积分方法

考虑一个具有非粘滞阻尼特性的多自由度系统响应的时程分析问题.该非粘滞阻尼模型假设阻尼力与质点速度的时间历程相关,数学表达式体现为阻尼力等于质点速度与某一核函数的卷积.在利用状态空间方法将系统运动方程转换成一阶的状态方程的基础上,采用精细积分方法对状态方程进行数值求解,得到一种求解该阻尼系统时程响应的精确、高效的计算方法.通过两个数值算例表明,采用该方法得到几乎精确的数值计算结果,而且计算效率有成数量级的提高.     

粘弹性固体的精细积分有限元算法

粘弹性固体本构方程的数学表达式分为微分型和积分型两种，其数值求解主要是时域上离散计算。文中从微分型表达式出发导出其状态空间方程的数学表达式，通过严格推导论证了它与微、积分型表达式的等价性；引入状态空间方程，从而利用精细积分格式来求解粘弹性固体本构方程；给出了粘弹性固体本构方程的精细积分有限元算法，为求解粘弹性固体本构方程的数值解提供了一个新的途径，具有计算简便，求解精度高等优点。     

非线性最小二乘跟踪的对偶变量变分方法

最小二乘跟踪方法是近几年提出的一种计算动力系统跟踪轨迹的方法.基于最小二乘跟踪的灵敏度分析算法可以有效避免传统的非线性系统灵敏度分析方法中的病态初值问题,因此其在混沌系统灵敏度分析方面有着重要的应用.针对非线性的最小二乘跟踪问题,首先将其重新描述为带有约束的非线性最优控制问题,引入协态变量并将系统的哈密顿函数表示为关于状态变量和协态变量的函数.然后将目标函数的积分时间离散化,根据对偶变量变分原理,以离散区间两端的状态变量作为独立变量,用Lagrange插值多项式近似离散区间内的状态变量和协态变量,进而将非线性最优控制问题转化为求解非线性方程组问题.这种算法无需对原问题做线性化处理,避免了复杂的线性化过程以及可能因此造成的误差,同时为求解非线性最小二乘跟踪问题提供了新的思路.根据最小二乘方法可以得到两条设计参数有微小变化的状态轨迹,基于这两条状态轨迹可进一步计算出系统关于设计参数的灵敏度,范德波振子作为数值算例验证了该方法在求解最小二乘跟踪问题以及计算非线性系统灵敏度时的有效性.      

基于Euler方程和离散共轭方法的气动外形优化设计

对于基于梯度信息的优化设计方法,很重要的一点是快速准确获得目标函数对设计变量的梯度.本文采用离散共轭方法计算目标函数关于设计变量的梯度,流动控制方程为三维Euler方程.对于离散共轭方程和流动控制方程均采用LU-SGS方法求解.算例表明,该方法能快速准确地获得目标函数的梯度.本文采用该方法进行了机翼和全机优化设计,成功地减弱了激波,降低了总阻力.算例证明了本文方法可靠性好,收敛快.     

基于随机响应面法的可靠性灵敏度分析及可靠性优化设计

基于随机响应面法建立了可靠性灵敏度分析方法,并将其用于结构可靠性优化设计。建立的方法利用随机响应面法将隐式的结构响应函数转换成显式函数,在显式的响应函数基础之上求解失效概率和进行可靠性灵敏度分析,得到的可靠性灵敏度能为基于函数梯度的优化算法提供梯度信息。算例表明,本文提出的可靠性灵敏度分析方法具有较高的效率和精度,提高了结构可靠性优化设计的效率。     

非确定性结构静动态特性稳健优化设计

本文研究了考虑参数随机性的结构静动态特性稳健性优化设计问题的数学模型和数值求解。在考虑结构设计变量和其研究了考虑参数随机性的结构静动态特性稳健性优化设计问题的数学模型和数值求 解. 在考虑结构设计变量和其他参数随机分布的前二阶矩的条件下，采用基于二阶摄动法的 随机有限元方法对结构响应的平均值和方差进行近似求解. 在摄动法有限元分析的框架下， 提出以一般函数形式表达的结构性能的平均值和标准差及其灵敏度的计算格式. 将结构 稳健性优化设计问题构造为双目标优化问题，优化目标包含结构性能函数的期望值和标准 差，约束函数的变异也给予考虑. 优化问题采用基于函数梯度的算法进行求解. 文中给出的数值算例显示了方法的有效性.     

Timoshenko梁谐响应求解新方法探索

在空间域上采用只与结点有关的无网格方法离散,在时间域上采用精细积分方法求 解. 无网格离散过程中,利用伽辽金积分等效弱形式代替微分形式的控制方程,并 用修正变分原理满足位移边界条件,采用移动最小二乘法求解离散的形函数,把形 函数代入等效积分弱形式得到离散的二阶方程;精细积分过程中非齐次项采 用Romberg积分. 同时给出了两种不同边界条件的谐响 应求解的两个数值算例,得到了精确的数值结果.     

响应面法在结构参数灵敏度及可靠性分析中的应用

采用Box-Behnken 矩阵设计方法进行试验设计,并根据设计点的响应,利用最小二乘回归法建立响应面函数. 将响应面函数中参数的梯度信息与其分散程度结合,得到各参数的灵敏度系数,再归一化灵敏度系数得到概率灵敏度;将响应面模型与一次二阶矩法相结合计算结构的可靠度. 针对一个具体算例,分别采用基于响应面法与基于ANSYS 的Monte Carlo 法计算了结构的灵敏度及可靠度值,结果的一致性验证了该方法的有效性.     

多体系统动力学动态最优化设计与灵敏度分析

基于多体系统的动态最优化设计过程包括传统的多体系统仿真分析、系统设计灵敏度分析、 系统最优化设计等过程, 针对多体系统运动学、用二阶常微分方程和微分代数方程描述 的动力学,基于含设计参数的通用数学模型及通用的积分型目标函数,采用高效的系统灵 敏度分析伴随变量方法及易于实施的惩罚函数最优设计方法,建立了多体系统最优设计数学 模型和算法. 通过双摆系统、曲柄-滑块系统、弹簧/阻尼器-滑块系统3个算例对上述 算法的有效性进行了验证.     

Direct sensitivity analysis of multibody systems with holonomic and nonholonomic constraints via an index-3 augmented Lagrangian formulation with projections

Optimizing the dynamic response of mechanical systems is often a necessary step during the early stages of product development cycle. This is a complex problem that requires to carry out the sensitivity analysis of the system dynamics equations if gradient-based optimization tools are used. These dynamics equations are often expressed as a highly nonlinear system of ordinary differential equations or differential-algebraic equations, if a dependent set of generalized coordinates with its corresponding kinematic constraints is used to describe the motion. Two main techniques are currently available to perform the sensitivity analysis of a multibody system, namely the direct differentiation and the adjoint variable methods. In this paper, we derive the equations that correspond to the direct sensitivity analysis of the index-3 augmented Lagrangian formulation with velocity and acceleration projections. Mechanical systems with both holonomic and nonholonomic constraints are considered. The evaluation of the system sensitivities requires the solution of a tangent linear model that corresponds to the Newton–Raphson iterative solution of the dynamics at configuration level, plus two additional nonlinear systems of equations for the velocity and acceleration projections. The method was validated in the sensitivity analysis of a set of examples, including a five-bar linkage with spring elements, which had been used in the literature as benchmark problem for similar multibody dynamics formulations, a point-mass system subjected to nonholonomic constraints, and a full-scale vehicle model.     

An adjoint method for the calculation of remote sensitivities in supersonic flow

This paper presents an adjoint method for the calculation of remote sensitivities in supersonic flow. The goal is to develop a set of discrete adjoint equations and their corresponding boundary conditions in order to quantify the influence of geometry modifications on the pressure distribution at an arbitrary location within the domain of interest. First, this paper presents the complete formulation and discretization of the discrete adjoint equations. The special treatment of the adjoint boundary condition to obtain remote sensitivities or sensitivities of pressure distributions at points remotely located from the wing surface are discussed. Secondly, we present results that demonstrate the application of the theory to a three-dimensional remote inverse design problem using a low sweep biconvex wing and a highly swept blunt leading edge wing. Lastly, we present results that establish the added benefit of using an objective function that contains the sum of the remote inverse and drag minimization cost functions.     

Multi-scaled analysis of the damped dynamics of an elastic rod with an essentially nonlinear end attachment

We study multi-frequency transitions in the transient dynamics of a viscously damped dispersive finite rod with an essentially nonlinear end attachment. The attachment consists of a small mass connected to the rod by means of an essentially nonlinear stiffness in parallel to a viscous damper. First, the periodic orbits of the underlying hamiltonian system with no damping are computed, and depicted in a frequency–energy plot (FEP). This representation enables one to clearly distinguish between the different types of periodic motions, forming back bone curves and subharmonic tongues. Then the damped dynamics of the system is computed; the rod and attachment responses are initially analyzed by the numerical Morlet wavelet transform (WT), and then by the empirical mode decomposition (EMD) or Hilbert–Huang transform (HTT), whereby, the time series are decomposed in terms of intrinsic mode functions (IMFs) at different characteristic time scales (or, equivalently, frequency scales). Comparisons of the evolutions of the instantaneous frequencies of the IMFs to the WT spectra of the time series enables one to identify the dominant IMFs of the signals, as well as, the time scales at which the dominant dynamics evolve at different time windows of the responses; hence, it is possible to reconstruct complex transient responses as superposition of the dominant IMFs involving different time scales of the dynamical response. Moreover, by superimposing the WT spectra and the instantaneous frequencies of the IMFs to the FEPs of the underlying hamiltonian system, one is able to clearly identify the multi-scaled transitions that occur in the transient damped dynamics, and to interpret them as ‘jumps’ between different branches of periodic orbits of the underlying hamiltonian system. As a result, this work develops a physics-based, multi-scaled framework and provides the necessary computational tools for multi-scaled analysis of complex multi-frequency transitions of essentially nonlinear dynamical systems.     

A methodology for the development of discrete adjoint solvers using automatic differentiation tools

A methodology for the rapid development of adjoint solvers for computational fluid dynamics (CFD) models is presented. The approach relies on the use of automatic differentiation (AD) tools to almost completely automate the process of development of discrete adjoint solvers. This methodology is used to produce the adjoint code for two distinct 3D CFD solvers: a cell-centred Euler solver running in single-block, single-processor mode and a multi-block, multi-processor, vertex-centred, magneto-hydrodynamics (MHD) solver. Instead of differentiating the entire source code of the CFD solvers using AD, we have applied it selectively to produce code that computes the transpose of the flux Jacobian matrix and the other partial derivatives that are necessary to compute sensitivities using an adjoint method. The discrete adjoint equations are then solved using the Portable, Extensible Toolkit for Scientific Computation (PETSc) library. The selective application of AD is the principal idea of this new methodology, which we call the AD adjoint (ADjoint). The ADjoint approach has the advantages that it is applicable to any set of governing equations and objective functions and that it is completely consistent with the gradients that would be computed by exact numerical differentiation of the original discrete solver. Furthermore, the approach does not require hand differentiation, thus avoiding the long development times typically required to develop discrete adjoint solvers for partial differential equations, as well as the errors that result from the necessary approximations used during the differentiation of complex systems of conservation laws. These advantages come at the cost of increased memory requirements for the discrete adjoint solver. However, given the amount of memory that is typically available in parallel computers and the trends toward larger numbers of multi-core processors, this disadvantage is rather small when compared with the very significant advantages that are demonstrated. The sensitivities of drag and lift coefficients with respect to different parameters obtained using the discrete adjoint solvers show excellent agreement with the benchmark results produced by the complex-step and finite-difference methods. Furthermore, the overall performance of the method is shown to be better than most conventional adjoint approaches for both CFD solvers used.     

Adjoint optimization of natural convection problems: differentially heated cavity

Optimization of natural convection-driven flows may provide significant improvements to the performance of cooling devices, but a theoretical investigation of such flows has been rarely done. The present paper illustrates an efficient gradient-based optimization method for analyzing such systems. We consider numerically the natural convection-driven flow in a differentially heated cavity with three Prandtl numbers (\(Pr=0.15{-}7\)) at super-critical conditions. All results and implementations were done with the spectral element code Nek5000. The flow is analyzed using linear direct and adjoint computations about a nonlinear base flow, extracting in particular optimal initial conditions using power iteration and the solution of the full adjoint direct eigenproblem. The cost function for both temperature and velocity is based on the kinetic energy and the concept of entransy, which yields a quadratic functional. Results are presented as a function of Prandtl number, time horizons and weights between kinetic energy and entransy. In particular, it is shown that the maximum transient growth is achieved at time horizons on the order of 5 time units for all cases, whereas for larger time horizons the adjoint mode is recovered as optimal initial condition. For smaller time horizons, the influence of the weights leads either to a concentric temperature distribution or to an initial condition pattern that opposes the mean shear and grows according to the Orr mechanism. For specific cases, it could also been shown that the computation of optimal initial conditions leads to a degenerate problem, with a potential loss of symmetry. In these situations, it turns out that any initial condition lying in a specific span of the eigenfunctions will yield exactly the same transient amplification. As a consequence, the power iteration converges very slowly and fails to extract all possible optimal initial conditions. According to the authors’ knowledge, this behavior is illustrated here for the first time.     

一种考虑瞬态效应的散热结构导热路径设计的拓扑优化模型

实际工程中,热载荷多数具有短时和周期性特点,瞬态效应显著。目前的散热结构导热路径设计多基于稳态热传导模型,未考虑瞬态效应。本文提出了一种以区域温度控制函数作为设计目标的瞬态热传导问题的拓扑优化模型,能够实现在整个时间历程上特定区域内最高温度最小。使用伴随变量法,推导了目标函数关于设计变量的敏度计算格式。算例表明,基于本文优化模型获得的散热路径设计与基于稳态热传导模型的结果有明显差别,具有更优的散热性能。因此,时变热荷载下的散热结构构型设计需要考虑瞬态响应的影响。     

Eigenvalue-counting methods for non-proportionally damped systems

This paper presents numerical methods of counting the number of eigenvalues for non-proportionally damped system in some interested regions on the complex plane. Most of the eigenvalue analysis methods for proportionally damped systems use the well-known Sturm sequence property to check the missed eigenvalues when only a set of the lowest modes is used. However, in the case of the non-proportionally damped systems such as the soil–structure interaction system, the structural control system and composite structures, no counterpart of the Sturm sequence property for undamped systems has been established yet. In this study, a numerical method based on argument principle is explained with emphasis on the discretization of the contour and a new method based on Gleyse’s theorem is proposed. To verify the applicability of the methods, two numerical examples are considered.     

Robust design in aerodynamics using third‐order sensitivity analysis based on discrete adjoint. Application to quasi‐1D flows

In this paper, the second‐order second moment approach, coupled with an adjoint‐based steepest descent algorithm, for the solution of the so‐called robust design problem in aerodynamics is proposed. Because the objective function for the robust design problem comprises first‐order and second‐order sensitivity derivatives with respect to the environmental parameters, the application of a gradient‐based method , which requires the sensitivities of this function with respect to the design variables, calls for the computation of third‐order mixed derivatives. To compute these derivatives with the minimum CPU cost, a combination of the direct differentiation and the discrete adjoint variable method is proposed. This is presented for the first time in the relevant literature and is the most efficient among other possible schemes on condition that the design variables are much more than the environmental ones; this is definitely true in most engineering design problems. The proposed approach was used for the robust design of a duct, assuming a quasi‐1D flow model; the coordinates of the Bézier control points parameterizing the duct shape are used as design variables, whereas the outlet Mach number and the Darcy–Weisbach friction coefficient are used as environmental ones. The extension to 2D and 3D flow problems, after developing the corresponding direct differentiation and adjoint variable methods and software, is straightforward. Copyright © 2011 John Wiley & Sons, Ltd.     

The independent set perturbation adjoint method: A new method of differentiating mesh‐based fluids models

A new scheme for differentiating complex mesh‐based numerical models (e.g. finite element models), the Independent Set Perturbation Adjoint method (ISP‐Adjoint), is presented. Differentiation of the matrices and source terms making up the discrete forward model is realized by a graph coloring approach (forming independent sets of variables) combined with a perturbation method to obtain gradients in numerical discretizations. This information is then convolved with the ‘mathematical adjoint’, which uses the transpose matrix of the discrete forward model. The adjoint code is simple to implement even with complex governing equations, discretization methods and non‐linear parameterizations. Importantly, the adjoint code is independent of the implementation of the forward code. This greatly reduces the effort required to implement the adjoint model and maintain it as the forward model continues to be developed; as compared with more traditional approaches such as applying automatic differentiation tools. The approach can be readily extended to reduced‐order models. The method is applied to a one‐dimensional Burgers' equation problem, with a highly non‐linear high‐resolution discretization method, and to a two‐dimensional, non‐linear, reduced‐order model of an idealized ocean gyre. Copyright © 2010 John Wiley & Sons, Ltd.     

Numerical Approaches to Optimal Control of a Model Equation for Shear Flow Instabilities

We investigate two different discretization approaches of a model optimal-control problem, chosen to be relevant for control of instabilities in shear flows. In the first method, a fully discrete approach has been used, together with a finite-element spatial discretization, to obtain the objective function gradient in terms of a discretely-derived adjoint equation. In the second method, Chebyshev collocation is used for spatial discretization, and the gradient is approximated by discretizing the continuously-derived adjoint equation. The discrete approach always results in a faster convergence of the conjugate-gradient optimization algorithm. Due to the shear in the convective velocity, a low diffusivity in the problem complicates the structure of the computed optimal control, resulting in particularly noticeable differences in convergence rate between the methods. When the diffusivity is higher, the control becomes less complicated, and the difference in convergence rate reduces. The use of approximate gradients results in a higher sensitivity to the degrees of freedom in time. When the system contains a strong instability, it only takes a few iteration to obtain an effective control for both methods,even if there are differences in the formal convergence rate. This indicates that it is possible to use the approximative gradients of the objective function in cases where the control problem mainly consists of controlling strong instabilities. This revised version was published online in July 2006 with corrections to the Cover Date.