Adaptive training of local reduced bases for unsteady incompressible Navier–Stokes flows

This report presents a numerical study of reduced‐order representations for simulating incompressible Navier–Stokes flows over a range of physical parameters. The reduced‐order representations combine ideas of approximation for nonlinear terms, of local bases, and of least‐squares residual minimization. To construct the local bases, temporal snapshots for different physical configurations are collected automatically until an error indicator is reduced below a user‐specified tolerance. An adaptive time‐integration scheme is also employed to accelerate the generation of snapshots as well as the simulations with the reduced‐order representations. The accuracy and efficiency of the different representations is compared with examples with parameter sweeps. Copyright © 2015 John Wiley & Sons, Ltd.     

Nonlinear model order reduction based on local reduced‐order bases

A new approach for the dimensional reduction via projection of nonlinear computational models based on the concept of local reduced‐order bases is presented. It is particularly suited for problems characterized by different physical regimes, parameter variations, or moving features such as discontinuities and fronts. Instead of approximating the solution of interest in a fixed lower‐dimensional subspace of global basis vectors, the proposed model order reduction method approximates this solution in a lower‐dimensional subspace generated by most appropriate local basis vectors. To this effect, the solution space is partitioned into subregions, and a local reduced‐order basis is constructed and assigned to each subregion offline. During the incremental solution online of the reduced problem, a local basis is chosen according to the subregion of the solution space where the current high‐dimensional solution lies. This is achievable in real time because the computational complexity of the selection algorithm scales with the dimension of the lower‐dimensional solution space. Because it is also applicable to the process of hyper reduction, the proposed method for nonlinear model order reduction is computationally efficient. Its potential for achieving large speedups while maintaining good accuracy is demonstrated for two nonlinear computational fluid and fluid‐structure‐electric interaction problems. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive greedy algorithms based on parameter-domain decomposition and reconstruction for the reduced basis method

The reduced basis method (RBM) empowers repeated and rapid evaluation of parametrized partial differential equations through an offline–online decomposition, a.k.a. a learning-execution process. A key feature of the method is a greedy algorithm repeatedly scanning the training set, a fine discretization of the parameter domain, to identify the next dimension of the parameter-induced solution manifold along which we expand the surrogate solution space. Although successfully applied to problems with fairly high parametric dimensions, the challenge is that this scanning cost dominates the offline cost due to it being proportional to the cardinality of the training set which is exponential with respect to the parameter dimension. In this work, we review three recent attempts in effectively delaying this curse of dimensionality, and propose two new hybrid strategies through successive refinement and multilevel maximization of the error estimate over the training set. All five offline-enhanced methods and the original greedy algorithm are tested and compared on two types of problems: the thermal block problem and the geometrically parameterized Helmholtz problem.     

A local multiple proper generalized decomposition based on the partition of unity

It is well known that model order reduction techniques that project the solution of the problem at hand onto a low-dimensional subspace present difficulties when this solution lies on a nonlinear manifold. To overcome these difficulties (notably, an undesirable increase in the number of required modes in the solution), several solutions have been suggested. Among them, we can cite the use of nonlinear dimensionality reduction techniques or, alternatively, the employ of linear local reduced order approaches. These last approaches usually present the difficulty of ensuring continuity between these local models. Here, a new method is presented, which ensures this continuity by resorting to the paradigm of the partition of unity while employing proper generalized decompositions at each local patch.     

Projection‐based model reduction for contact problems

To be feasible for computationally intensive applications such as parametric studies, optimization, and control design, large‐scale finite element analysis requires model order reduction. This is particularly true in nonlinear settings that tend to dramatically increase computational complexity. Although significant progress has been achieved in the development of computational approaches for the reduction of nonlinear computational mechanics models, addressing the issue of contact remains a major hurdle. To this effect, this paper introduces a projection‐based model reduction approach for both static and dynamic contact problems. It features the application of a non‐negative matrix factorization scheme to the construction of a positive reduced‐order basis for the contact forces, and a greedy sampling algorithm coupled with an error indicator for achieving robustness with respect to model parameter variations. The proposed approach is successfully demonstrated for the reduction of several two‐dimensional, simple, but representative contact and self contact computational models. Copyright © 2015 John Wiley & Sons, Ltd.     

On the use of modal derivatives for nonlinear model order reduction

Modal derivative is an approach to compute a reduced basis for model order reduction of large‐scale nonlinear systems that typically stem from the discretization of partial differential equations. In this way, a complex nonlinear simulation model can be integrated into an optimization problem or the design of a controller, based on the resulting small‐scale state‐space model. We investigate the approximation properties of modal derivatives analytically and thus lay a theoretical foundation of their use in model order reduction, which has been missing so far. Concentrating on the application field of structural mechanics and structural dynamics, we show that the concept of modal derivatives can also be applied as nonlinear extension of the Craig–Bampton family of methods for substructuring. We furthermore generalize the approach from a pure projection scheme to a novel reduced‐order modeling method that replaces all nonlinear terms by quadratic expressions in the reduced state variables. This complexity reduction leads to a frequency‐preserving nonlinear quadratic state‐space model. Numerical examples with carefully chosen nonlinear model problems and three‐dimensional nonlinear elasticity confirm the analytical properties of the modal derivative reduction and show the potential of the proposed novel complexity reduction methods, along with the current limitations. Copyright © 2016 John Wiley & Sons, Ltd.     

基于微滑移模型的B-G型叶片干摩擦缘板阻尼器减振特性研究

在干摩擦接触面间引入弹性剪切层来模拟干摩擦接触,考虑摩擦接触界面在振动过程中可能经历完全粘滞、局部滑移、完全滑移三个阶段,提出一种改良的微滑移摩擦阻尼模型。在该阻尼模型基础上对摩擦力-位移迟滞曲线进行了仿真,得到了符合工程实际的迟滞曲线;分析了不同外力下接触面上的摩擦分布,揭示了微滑移模型的本质;利用一次谐波平衡与等效线性化相结合,研究多种参数对阻尼器等效刚度和等效阻尼及减振特性的影响,得到的减振规律为工程中该类阻尼器设计提供了指导。     

Reduced order model assisted evolutionary algorithms for multi-objective flow design optimization

Evolutionary algorithms (EAs) have been widely used for flow design optimization problems for their well-known robustness and derivative-free property as well as their advantages in dealing with multi-objective optimization problems and providing global optimal solutions. However, EAs usually involve a large number of function evaluations that are sometimes quite time consuming. In this article a reduced order modelling technique that combines proper orthogonal decomposition and radial basis function interpolation is developed to reduce the computational cost. These models provide an efficient way to simulate the whole flow region with varied geometry parameters instead of solving partial differential equations. As a test case, the design optimization of a heat exchanger is considered. Shape variation is conducted through a free form deformation technique, which deforms the computational grid employed by the flow solver. A comparison between the optimization results when using reduced order models and the exact flow solver is presented.     

Rapid free-vibration analysis with model reduction based on coherent nodal clusters

Modal expansion is a workhorse used in many engineering analysis algorithms. One example is the coupled boundary element-finite element computation of the backscattering target strength of underwater elastic objects. To obtain the modal basis, a free-vibration (generalized eigenvalue) problem needs to be solved, which tends to be expensive when there are many basis vectors to compute. In the above-mentioned backscattering example it could be many hundreds or thousands. Excellent algorithms exist to solve the free-vibration problem, and most use some form of the Rayleigh-Ritz (RR) procedure. The key to an efficient RR application is a low-cost transformation into a reduced basis. In this work, a novel, inexpensive a priori transformation is constructed for solid-mechanics finite element models based on the notion of coherent nodal clusters. The inexpensive RR procedure then leads to significant speedups of the computation of an approximate solution to the free vibration problem.     

局部约束结构振动的模态研究

制动盘/摩擦块系统的制动过程属于局部接触振动问题。摩擦块局部接触(约束)会对系统模态及固有频率造成影响,进而影响制动噪声的产生。将刹车盘简化为一维循环梁结构,并建立了在摩擦块作用下的运动方程。首先计算无接触时梁自由振动的模态(参考模态)。然后用线性弹簧代替局部接触,列写出连续条件并计算模态,得到所谓局部非连续基函数。将局部非连续基函数与参考模态进行正交化处理后,作为参考模态的补充,用于计算系统响应。与差分法结果比较表明,与传统模态方法相比,局部非连续基函数法更为准确。研究发现局部接触会抑制循环结构振动的对称性,导致正弦或余弦模态消失,以及刚度非线性和摩擦作用,会使振动是波动型的。该工作为基于局部非连续基函数法研究摩擦结构不稳定振动机理打下了基础。     

Proper orthogonal decomposition‐based model order reduction via radial basis functions for molecular dynamics systems

Model order reduction for molecular dynamics (MD) systems exhibits intrinsic complexities because of the highly nonlinear and nonlocal multi‐atomic interactions in high dimensions. In the present work, we introduce a proper orthogonal decomposition‐based method in conjunction with the radial basis function (RBF) approximation of the nonlinear and nonlocal potential energies and inter‐atomic forces for MD systems. This approach avoids coordinate transformation between the physical and reduced‐order coordinates, and allows the potentials and inter‐atomic forces to be calculated directly in the reduced‐order space. The RBF‐approximated potential energies and inter‐atomic forces in the reduced‐order space are discretized on the basis of the Smolyak sparse grid algorithm to further enhance the effectiveness of the proposed method. The good approximation properties of RBFs in interpolating scattered data make them ideal candidates for the reduced‐order approximation of MD inter‐atomic force calculations. The proposed approach is validated by performing the reduced‐order simulations of DNA molecules under various external loadings. Copyright © 2013 John Wiley & Sons, Ltd.     

Model order reduction based on successively local linearizations for flexible multibody dynamics

An efficient method of model order reduction is proposed for the dynamic computation of a flexible multibody system undergoing both large overall motions and large deformations. The system is initially modeled by using the nonlinear finite elements of absolute nodal coordinate formulation and then locally linearized at a series of quasi-static equilibrium configurations according to the given accuracy in dynamic computation. By using the Craig-Bampton method, the reduced model is established by projecting the incremental displacements of the locally linearized system onto a set of local modal bases at the quasi-static equilibrium configuration accordingly. Afterwards, the initial conditions for the dynamic computation for the reduced model via the generalized-α integrator can be determined from the modal bases. The analysis of computation complexity is also performed. Hence, the proposed method gives time-varying and dimension-varying modal bases to elaborate the efficient model reduction. Finally, three examples are presented to validate the accuracy and efficiency of the proposed method.     

The extended finite element method combined with a modal synthesis approach for vibro‐acoustic problems

The optimization of a vibro‐acoustic problem is of main importance for passengers' comfort in transportation vehicles in terms of interior noise. Engineers use numerical tools to predict the response of this coupled problem, but it may lead to a prohibitive computational time. Based on FEM, this work aims at reducing the computational time. The first idea is to keep the same mesh of the acoustic cavity for all the structure configurations and to enrich the pressure approximation by using the extended FEM (XFEM). The enrichment is based on a Heaviside function completed at the structure tip by a continuous ramp function. The second idea is to build reduced basis. The structure basis is composed of its eigenmodes, whereas a modal synthesis method with a fixed interface is used to build the fluid basis. The interface DOFs are the enriched DOF of the XFEM, whereas the internal domain corresponds to the acoustic cavity with no structure. These two combined ideas enable to minimize the computational time in the study of the influence of the structure positions in an acoustic cavity. The method is implemented for shell structures embedded in a 3D acoustic domain. Copyright © 2014 John Wiley & Sons, Ltd.     

采用基于KPOD的模型降阶方法提高油藏模拟速度的研究

应用场型了型降阶技术进行了传统油藏模拟器运算速度的研究。考虑到该技术采用本征正交分解(POD)方法能够加速模拟器运算,但对系统的输入参!较敏感,降低模拟的精度和效率,采用了基于Krylov子空间和POD的KPOD方法,以便利用Arnoldi的矩匹配性质和POD的数据泛化能力减少POD方法对模型输入参数的依赖。油藏模拟实例■,KPOD方法在计算速度和精度上都优于POD方法,验证了该方法的有效性和实用性。     

基于MBC的模型结构振动控制实验研究

基于市场机制控制策略（Market-based control, MBC）是一种多目标优化算法。为检验MBC在实际结构振动控制中的控制效果,本文进行了基于MBC的模型结构振动控制实验研究。实验选用压电陶瓷片作为驱动单元和传感单元,在dSpace系统平台下,结合Matlab/Simulink工作环境,完成了MBC控制算法在实际模型振动控制中的应用。实验过程中分别对自由振动（无控）状态下和MBC控制状态下的模型结构进行了振动反应测试,获得了模型结构在输入同一正弦激励后自由振动与MBC控制状态下的结构振动响应,并对实验结果进行了对比分析。实验结果表明,MBC算法应用于实际结构中具有较好的减振控制效果     

Parameter estimation with model order reduction for elliptic differential equations

In this paper a new method for parameter estimation for elliptic partial differential equations is introduced. Parameter estimation includes minimizing an objective function, which is a measure for the difference between the parameter-dependent solution of the differential equation and some given data. We assume, that the given data results in a good approximation of the state of the system.In order to evaluate the objective function the solution of a differential equation has to be computed and hence, a large system of linear equations has to be solved. Minimization methods involve many evaluations of the objective function and therefore, the differential equation has to be solved multiple times. Thus, the computing time for parameter estimation can be large. Model order reduction was developed in order to reduce the computational effort of solving these differential equations multiple times. We use the given approximation of the state of the system as reduced basis and omit computing any snapshots. Therefore, our approach decreases the effort of the offline phase drastically. Furthermore, the dimension of the reduced system is one and thus, is much smaller than the dimension of other approaches. However, the obtained reduced model is a good approximation only close to the given data. Hence, the reduced system can lead to large errors for parameter sets, which correspond to solutions far away from the given approximation of the state of the system. In order to prevent convergence of the parameter estimator to such a local minimizer we penalise the approximation error between the full and the reduced system.     

Reduced basis approximation and a posteriori error estimation for stress intensity factors

We develop reduced basis approximations, rigorous a posteriori error bounds, and offline–online computational procedures for the accurate, fast, and reliable prediction of stress intensity factors or strain energy release rates for ‘Mode I’ linear elastic crack problems relevant to fracture mechanics. We demonstrate the efficiency and rigor of our numerical method in several examples. Copyright © 2007 John Wiley & Sons, Ltd.     

Singularity extraction technique for integral equation methods with higher order basis functions on plane triangles and tetrahedra

A numerical solution of integral equations typically requires calculation of integrals with singular kernels. The integration of singular terms can be considered either by purely numerical techniques, e.g. Duffy's method, polar co‐ordinate transformation, or by singularity extraction. In the latter method the extracted singular integral is calculated in closed form and the remaining integral is calculated numerically. This method has been well established for linear and constant shape functions. In this paper we extend the method for polynomial shape functions of arbitrary order. We present recursive formulas by which we can extract any number of terms from the singular kernel defined by the fundamental solution of the Helmholtz equation, or its gradient, and integrate the extracted terms times a polynomial shape function in closed form over plane triangles or tetrahedra. The presented formulas generalize the singularity extraction technique for surface and volume integral equation methods with high‐order basis functions. Numerical experiments show that the developed method leads to a more accurate and robust integration scheme, and in many cases also a faster method than, for example, Duffy's transformation. Copyright © 2003 John Wiley & Sons, Ltd.     

An implicit upwinding volume element method based on meshless radial basis function techniques for modelling transport phenomena

This work presents a control volume (CV) method for transient transport problems where the cell surface fluxes are reconstructed using local interpolation functions that besides interpolating the nodal values of the field variable, also satisfies the governing equation at some auxiliary points in the interpolation stencils. The interpolation function relies on a Hermitian radial basis function (HRBF) meshless collocation approach to find the solution of auxiliary local boundary/initial value problems, that are solved using the same time‐integration scheme adopted to update the global CV solution. By the use of interpolation functions that approximate the governing equation a form of analytical upwinding scheme is achieved, without the need of using predefined interpolation stencils according to the magnitude and direction of the local advective velocity. In this way, the interpolation formula retains the desired information about the advective velocity field allowing the use of centrally defined stencils even in the cases of advective dominant problems. This new CV approach is referred to as the CV‐HRBF method. Two time‐stepping formulations are considered: a full implicit approach and the weighted Crank–Nicholson one. The implicit upwinding scheme, intrinsic to the proposed CV‐HRBF, is tested by solving a travelling front problem at the Péclet number equal to 500, 1000 and infinity; with the latter corresponding to a shock front. Finally, the accuracy of the numerical method is validated against one‐ and three‐dimensional reactive transport problems characterized by smooth solutions. Copyright © 2009 John Wiley & Sons, Ltd.     

基于ICMCM法的GARTEUR结构有限元模型修正研究

摘要：改进的正交模型正交模态 (ICMCM) 法在进行模型修正过程中需要同时使用实验测得的频率及模态振型等数据。本文利用有限元模型的模态振型代替实验测量的模态振型并通过迭代解决了模型修正过程中缺少实验模态振型数据的问题,使ICMCM法具有更广的应用范围。根据国际认可的三级评价标准使用ICMCM法对GARTEUR飞机模型进行了修正,并与国际上其他单位的模型修正结果进行横向比较,结果证明了本文改进方法的可行性及修正结果的优越性。