Multifidelity adaptive kriging metamodel based on discretization error bounds

This article presents an approach to build a multifidelity kriging metamodel from finite element computations on different meshes for stuctural reliability assessment. The proposed method takes advantage of the computation of bounds on the discretization error, which enables to guarantee the state (safe or failure) of each computation of the performance function. An algorithm to build the metamodel from the different levels of fidelity and estimate the failure probability is provided. Illustrations are presented on a two dimensional mechanical crack opening problem. Bounds on the failure probability are also post-processed.     

Iterative solution of the random eigenvalue problem with application to spectral stochastic finite element systems

A new algorithm for the computation of the spectral expansion of the eigenvalues and eigenvectors of a random non‐symmetric matrix is proposed. The algorithm extends the deterministic inverse power method using a spectral discretization approach. The convergence and accuracy of the algorithm is studied for both symmetric and non‐symmetric matrices. The method turns out to be efficient and robust compared to existing methods for the computation of the spectral expansion of random eigenvalues and eigenvectors. Copyright © 2006 John Wiley & Sons, Ltd.     

Practical fully three-dimensional reconstruction algorithms for diffuse optical tomography

We have developed an efficient fully three-dimensional (3D) reconstruction algorithm for diffuse optical tomography (DOT). The 3D DOT, a severely ill-posed problem, is tackled through a pseudodynamic (PD) approach wherein an ordinary differential equation representing the evolution of the solution on pseudotime is integrated that bypasses an explicit inversion of the associated, ill-conditioned system matrix. One of the most computationally expensive parts of the iterative DOT algorithm, the reevaluation of the Jacobian in each of the iterations, is avoided by using the adjoint-Broyden update formula to provide low rank updates to the Jacobian. In addition, wherever feasible, we have also made the algorithm efficient by integrating along the quadratic path provided by the perturbation equation containing the Hessian. These algorithms are then proven by reconstruction, using simulated and experimental data and verifying the PD results with those from the popular Gauss-Newton scheme. The major findings of this work are as follows: (i) the PD reconstructions are comparatively artifact free, providing superior absorption coefficient maps in terms of quantitative accuracy and contrast recovery; (ii) the scaling of computation time with the dimension of the measurement set is much less steep with the Jacobian update formula in place than without it; and (iii) an increase in the data dimension, even though it renders the reconstruction problem less ill conditioned and thus provides relatively artifact-free reconstructions, does not necessarily provide better contrast property recovery. For the latter, one should also take care to uniformly distribute the measurement points, avoiding regions close to the source so that the relative strength of the derivatives for measurements away from the source does not become insignificant.     

A greedy MLPG method for identifying a control parameter in 2D parabolic PDEs

In this paper, we consider coefficient inverse problems, which are associated with the identification of unknown time dependent control parameter and unknown solution of two-dimensional parabolic inverse problem with overspecialization at a point in the spatial domain. After suitable finite difference approximation of time variable, an MLPG method is used for spatial discretization. To improve the efficiency of the MLPG method, a greedy algorithm is used. In fact, using the greedy algorithm, we avoid using more points from the data site than absolutely necessary and therefore, the method becomes more efficient. Comparison of the different kind of point selection and the effect of noisy data are performed for four test problems while our last test problem considers a problem with unknown solution. The results reveal that the method is efficient.     

ERROR ESTIMATION AND ADAPTIVITY IN ELASTOPLASTICITY

In this paper, a method is developed to control the parameters of a finite element computation for time-dependent material models. This method allows the user to obtain a prescribed accuracy with a computational cost as low as possible. To evaluate discretization errors, we use a global error measure in constitutive relation based on Drucker's inequality. This error includes, over the studied time interval, the error of the finite element model and the error of the algorithm being used. In order to master the size of the elements of the mesh and the length of the time increments, an error estimator, which permits estimating the errors due to the time discretization, is proposed. These tools are used to elaborate two procedures of adaptivity. Various examples for monotonous or non-monotonous loadings, for 2-D or axisymmetric problems, show the reliability of these procedures.     

Robust inference of baseline optical properties of the human head with three-dimensional segmentation from magnetic resonance imaging

We model the capability of a small (6-optode) time-resolved diffuse optical tomography (DOT) system to infer baseline absorption and reduced scattering coefficients of the tissues of the human head (scalp, skull, and brain). Our heterogeneous three-dimensional diffusion forward model uses tissue geometry from segmented magnetic resonance (MR) data. Handling the inverse problem by use of Bayesian inference and introducing a realistic noise model, we predict coefficient error bars in terms of detected photon number and assumed model error. We demonstrate the large improvement that a MR-segmented model can provide: 2-10% error in brain coefficients (for 2 x 10(6) photons, 5% model error). We sample from the exact posterior and show robustness to numerical model error. This opens up the possibility of simultaneous DOT and MR for quantitative cortically constrained functional neuroimaging.     

OFDM系统符号定时精同步研究

基于时域的帧同步估计算法在通过高斯信道和多径衰落信道时,其时间测度由于循环前缀的影响有峰值平台,难于准确的判定帧到达的时刻。文中提出了一种低复杂度的符号定时估计算法,利用简化的时间测度函数检测峰值来实现同步。分析了该算法的性能,并在各种信道中进行了性能分析,给出了了仿真结果。结果表明,该算法具有较高的精度和较低的计算复杂度。     

Bearing dynamic parameters identification of a flexible rotor-bearing system based on transfer matrix method

Bearing dynamic parameters are important factors governing the vibration characteristics of rotating machinery; however, they are difficult to determine due to limited experimentation, and inaccurate in modelling. In this paper, a parameter identification method is presented to identify the bearing dynamic parameters of a flexible rotor-bearing system. In this method, the parameter identification problem is formulated as an inverse problem. The bearing dynamic parameters have been characterized through minimizing the error squared of the rotor-bearing system unbalance response between the experiment results and the computational ones. The intergeneration projection genetic algorithm is used to minimize the error squared. As an efficient method for analysing the dynamic behaviour of a rotor-bearing system, an improved transfer matrix method has been employed to calculate the unbalance response. This approach has been applied to identify the bearing dynamic parameters of a test rig supported by two anisotropic bearings, according to the unbalance response experimental data. Results indicated that this method could identify the bearing dynamic parameters. It is also robust to the noise effects.     

Simultaneous inversion for the diffusion and source coefficients in the multi-term TFDE

This article deals with an inverse problem of determining the space-dependent diffusion coefficient and the source coefficient simultaneously in the multi-term time fractional diffusion equation (TFDE in short) using measurements at one inner point. From a view point of optimality, solving the inverse problem is transformed to minimize an error functional with the help of the solution operator from the unknown to the additional observation. The solution operator is nonlinear but it is of Lipschitz continuity by which existence of a minimum to the error functional is obtained using Sobolev embedding theorems. The homotopy regularization algorithm is introduced to solve the simultaneous inversion problem based on the minimization problem, and numerical examples are presented. The inversion solutions give good approximations to the exact solutions demonstrating that the homotopy regularization algorithm is efficient for the simultaneous inversion problem arising in the multi-term TFDE.     

3-D eddy-current computation with a self-adaptive refinementtechnique

A method for the adaptive computation of 3-D eddy-current problems is presented. The 3-D eddy-current problem is formulated in terms of the electric intensity (E formulation). Edge elements that impose tangential continuity of the approximation function are employed for the discretization of the problem with the finite element method. An a-posteriori error estimation technique is proposed with the introduction of two error criteria: a) the tangential discontinuity of the magnetic intensity H, and b) the normal discontinuity of the eddy current density J_e. The proposed error estimation technique is employed in a 3-D self-adaptive refinement procedure. Sufficient approximation of the skin effect and calculation of the eddy current distribution is obtained with the proposed method. The implementation of the proposed technique in a problem of 3-D eddy-current computation in a multiply connected conducting body is discussed     

Stochastic approach in the efficient design of the direct-binary-search algorithm for hologram synthesis

An algorithm incorporating a stochastic approach is proposed for reducing the computation time of the direct-binary-search algorithm for hologram synthesis. Two variants of this new algorithm are considered for a number of hologram-generation problems. Both variants can reduce the computation time significantly with a very small increase in the reconstruction error on average. The effectiveness of the proposed algorithm is found to improve with the increasing computational complexity of the design problem. Also, the algorithm is able to generate the hologram in a time that is relatively independent of the initial conditions.     

A General Algorithm of Rotating/tilting Positioner InverseKinematics for Robotic Arc Welding Off-line Programming

Off-line programming provides an essential link between CAD and CAM, whose development should result in greater use of robotic arc welding. An arc welding system with a robot and a rotating/tilting positioner is a major application area, where manual programming is a very tedious job. Off-line programming is a constructive way to solve the problem. The inverse kinematics algorithm of robot and positioner is the foundation of the off-line programming system. Although previously there were some researchers who studied the positioner inverse kinematics algorithm, they only focused on a special solution of the positioner inverse kinematics, which is the solution at down-hand welding position. However, in welding production, welding position other than down-hand position is also needed. A method for representing welding position was introduced. Then a general algorithm of rotating/tilting positioner inverse kinematics is presented.     

An improvement of the EDI method in linear elastic fracture mechanics by means of an a posteriori error estimator in G

In this paper, an error estimator that quantifies the effect of the finite element discretization error on the computation of the stress intensity factor in linear elastic fracture mechanics is presented. In order to obtain the proposed estimator, a shape design sensitivity analysis (SDSA) is applied to the fracture mechanics problem. Following this approach, one of the most efficient post‐processing techniques for computing the strain energy release rate G, the well‐known EDI method, may be interpreted as a continuum method of the SDSA. The proposed error estimator is based on the recovery of the gradient fields and its reliability has been checked by means of numerical problems, yielding very good estimations of the true error. The new estimator remarkably improves the results given by a previous error estimator, which is based on a discrete analytical approach of SDSA. As a consequence, the combination of the new error estimator and the result given by the EDI method provides a much more accurate estimation of G. Copyright © 2003 John Wiley & Sons, Ltd.     

Multivariate numerical derivative by solving an inverse heat source problem

A method for approximating multivariate numerical derivatives is presented from multidimensional noise data in this paper. Starting from solving a direct heat conduction problem using the multidimensional noise data as an initial condition, we conclude estimations of the partial derivatives by solving an inverse heat source problem with an over-specified condition, which is the difference of the solution to the direct problem and the given noise data. Then, solvability and conditional stability of the proposed method are discussed for multivariate numerical derivatives, and a regularized optimization is adopted for overcoming instability of the inverse heat source problem. For achieving partial derivatives successfully and saving amount of computation, we reduce the multidimensional problem to a one-dimensional case, and give a corresponding algorithm with a posterior strategy for choosing regularization parameters. Finally, numerical examples show that the proposed method is feasible and stable to noise data.     

CALCULATION OF THE STRESS INTENSITY FACTOR AND ESTIMATION OF ITS ERROR BY A SHAPE SENSITIVITY ANALYSIS

Abstract— The precision with which the stress intensity factor (SIF) can be calculated from a finite element solution depends essentially on the extraction method and on the discretization error. In this paper, the influence of the discretization error in the SIF calculation was studied and a method for estimating the resulting error was developed. The SIF calculation method used is based on a shape design sensitivity analysis; this assures that the resulting error in the extracted SIF depends solely on the global discretization error present in the finite element solution. Moreover, this method allows us to extend the Zienkiewicz-Zhu discretization error estimator to the SIF calculation. The reliability of the proposed method was analysed solving a two-dimensional problem using an h -adaptive process. Also the convergence of the error with the h -adaptive refinement was studied.     

Regularization of the inverse heat conduction problem by the discrete Fourier transform

Two methods of solving the inverse heat conduction problem with employment of the discrete Fournier transform are presented in this article. The first one operates similarly to the SVD algorithm and consists in reducing the number of components of the discrete Fournier transform which are taken into account to determine the solution to the inverse problem. The second method is related to the regularization of the solution to the inverse problem in the discrete Fournier transform domain. Those methods were illustrated by numerical examples. In the first example, an influence of the boundary conditions disturbance by a random error on the solution to the inverse problem (its stability) was examined. In the second example, the temperature distribution on the inner boundary of the multiply connected domain was determined. Results of calculations made in both ways brought very good outcomes and confirm the usefulness of applying the discrete Fournier transform to solving inverse problems.     

Certified real-time shape optimization using isogeometric analysis,PGD model reduction,and a posteriori error estimation

In this paper, we address the effective and accurate solution of problems with parameterized geometry. Considering the attractive framework of isogeometric analysis, which enables a natural and flexible link between computer-aided design and simulation tools, the parameterization of the geometry is defined on the mapping from the isogeometric analysis parametric space to the physical space. From the subsequent multidimensional problem, model reduction based on the proper generalized decomposition technique with off-line/online steps is introduced in order to describe the resulting manifold of parametric solutions with reduced CPU cost. Eventually, a posteriori estimation of various error sources inheriting from discretization and model reduction is performed in order to control the quality of the approximate solution, for any geometry, and feed a robust adaptive algorithm that optimizes the computational effort for prescribed accuracy. The overall approach thus constitutes an effective and reliable numerical tool for shape optimization analyses. Its performance is illustrated on several two- and three-dimensional numerical experiments.     

Using mesh adaption for the identification of a spatial field of material properties

It is well known that the solution of an inverse problem is ill‐posed and not unique. To avoid difficulties caused by this, when solving such a problem, Tikhonov's regularization terms are usually added to the norm quantifying the discrepancy between the model's predictions and experimental data. This regularization term however is often inadequate to perform the identification of a field of material properties that varies spatially. This is all the more difficult when dealing with the numerical solution of this inverse problem, for the sought field is spatially discretized and this discretization can influence the result of the identification. We will here examine an overall strategy using classical adaptive meshing methods used to circumvent these drawbacks. The first step consists of using two distinct meshes: one associated with the discretization of the sought spatial field and the other associated with the solution of the mechanical problems (forward and adjoint states). In the second step, we will introduce local error estimators that allow an oriented refinement of the mesh associated with the sought parameters. This general strategy is applied to a practical case study: the detection of underground cavities using experimental data obtained by an interferometric device on a satellite. We will then address the question of how the regularization terms and the error estimator driving the mesh refinement were selected. Copyright © 2011 John Wiley & Sons, Ltd.     

一种高效的FE-PSBFE耦合方法及在岩土工程弹塑性分析中的应用

针对复杂岩土工程结构建模困难、耗时费力的难题,结合八叉树网格离散技术,对网格中的六面体采用等参单元,对于非六面体采用多面体比例边界有限单元（PSBFE）,建立了一种快速、高效的FE-PSBFE弹塑性耦合数值分析方法。采用实现的PSBFE对标准土石坝进行数值模拟,验证了其正确性和计算精度;通过典型复杂心墙坝对提出FE-PSBFE耦合方法的灵活性、通用性和高效性进行了研究,研究结果表明:与传统FEM相比,该耦合方法可大幅加速模型前处理进程,解决了复杂三维空间河谷形状、水平分层填筑和材料分区导致的网格剖分难题,几十万单元的网格划分一般仅需几分钟;与PSBFE相比,显著提高了岩土结构弹塑性分析的效率,FE-PSBFE可减少超过80%的求解时间。FE-PSBFE耦合方法对其他复杂几何条件的工程问题也具有良好的实用性,为快速精细化抗震分析提供了技术手段。     

An inverse problem approach to optical homodyne tomography

Abstract

The problem of optical homodyne tomography is considered in the context of a Bayesian model-fitting or inverse problem approach. An algorithm is formulated, based on matrix computation rather than the numerical approximation of an analytic inverse transform. This automatically takes into account the effects of noise, detector inefficiencies and incomplete sampling of the data. The relationships with conventional reconstruction schemes, methods for including various forms of prior information and for calculating error estimates are discussed. The process of reconstructing the photon number distribution and the density matrix are illustrated using both simulated and experimental data.