Three-dimensional electromagnetic nonlinear inversion in layered media by a hybrid diagonal tensor approximation: Stabilized biconjugate gradient fast Fourier transform method

This paper presents an efficient three-dimensional nonlinear electromagnetic inversion method in a multilayered medium for radar applications where the object size is comparable to the wavelength. In the first step of this two-step inversion algorithm, the diagonal tensor approximation is used in the Born iterative method. The solution of this approximate inversion is used as an initial guess for the second step in which further inversion is carried out using a distorted Born iterative method. Since the aim of the second step is to improve the accuracy of the inversion, a full-wave solver, the stabilized biconjugate-gradient fast Fourier transform algorithm, is used for forward modelling. The conjugate-gradient method is applied at each inversion iteration to minimize the functional cost. The usage of an iterative solver based on the FFT algorithm and the developed recursive matrix method combined with an interpolation technique to evaluate the layered medium Green's functions rapidly, makes this method highly efficient. An inversion problem with 32 768 complex unknowns can be solved with 1% relative error by using a simple personal computer. Several numerical experiments for arbitrarily located source and receiver arrays are presented to show the high efficiency and accuracy of the proposed method.     

QL-Born迭代法电磁散射计算

积分方程法是多维电磁响应的数值模拟和反演计算的有效方法之一.在线性化散射电磁场积分方程的基础上,采用迭代Born近似法进行了电导率成像反演.针对迭代Born近似法反演依赖初始模型,而QL近似法无需给定初值的特点,提出了两步法(QL-Born迭代法),用QL近似法计算的结果作为Born迭代法的初始模型,避免人为设置初值,并进行了数值实验.     

各向异性介质三维电磁响应模拟的Ho-GEBA算法

本文基于积分方程法研究并建立了一种模拟横向同性介质中任意各向异性异常 体三维电磁响应的高阶广义扩展Born近似(Ho-GEBA)算法. 首先利用逐次迭代技术给出积分方程的广义级数展开解, 为保证其收敛性, 引入一种各向异性条件下满足压缩映射的迭代算子. 然后利用异常体区域分解技术, 并结合扩展Born近似原理, 得到各向异性介质三维电磁响应的Ho-GEBA解. 为提高效率, 计算过程中采用并矢Green函数的解析表达式. 最后通过数值计算实例对比验证了本文算法的有效性. 关键词： 高阶广义扩展Born近似 积分方程 电磁模拟 解析Green函数     

基于逆散射理论的地震波速度正则化反演

本文基于逆散射理论利用正则化有限差分对比源反演算法对地震波传播速度进行反演, 该方法是基于波动方程的频率域波形反演算法, 利用非线性共轭梯度法, 通过最小化目标优化函数不断迭代更新速度模型. 由于地球物理反演问题的病态性和不稳定性, 通过基于反演参数总变差的正则化处理, 使反演问题变为良性问题且算法具有较强的抗噪声干扰能力. 反演过程中使用了频率-空间域9点差分正演算子以及PML吸收边界条件. 与其他反演算法相比, 由于背景模型在反演迭代过程中保持不变, 可以避免在每次迭代过程中重新构造正演算子及矩阵分解等相关计算过程, 使得该算法非常适合于大规模三维反演计算. 此外, 本文采用基于MPI的并行计算, 进一步提高了反演计算的效率. 二维CSEG模型反演结果表明该方法可以反演得到高分辨率的地震波速度重建结果, 为地震勘探数据处理及解释提供准确的速度信息.     

Conditional Source-term Estimation using dynamic ensemble selection and parallel iterative solution

A modified version of the Least-Square QR-factorisation (LSQR) algorithm has been implemented in conjunction with Conditional Source-term Estimation (CSE) for lean, turbulent premixed methane–air combustion via Large Eddy Simulation (LES). The iterative solver can reduce computational times by an order of magnitude during the inversion phase of CSE in comparison with the conventional LU-decomposition method. The advantages of iterative and parallel iterative solvers become more prominent as the size of the system increases. The ensemble selection procedure for computing averages within localised regions of the simulation domain has also been updated to a dynamic routine. This allows for more flexible and efficient allocation of computational resources along with reduced input from the user, especially for complex geometries. Preliminary LES calculations have shown that the implementation of an iterative solver and a dynamic ensemble selection algorithm will reduce computational times significantly with negligible error contribution for one-condition CSE, which is applicable to purely premixed or non-premixed turbulent combustion problems. In addition, these algorithms provide the foundation for exceptional computational cost savings for the inversion in two-condition CSE, or Doubly Conditional Source-term Estimation (DCSE), which has shown promise for predicting partially-premixed combustion. Parallel computation of the inverse solution is particularly beneficial to DCSE as the computational cost of the inversion process is considerably larger than in one-condition CSE.     

The Riemann Problem for the one-dimensional,free-surface Shallow Water Equations with a bed step: Theoretical analysis and numerical simulations

In this paper, the solution of the Riemann Problem for the one-dimensional, free-surface Shallow Water Equations over a bed step is analyzed both from a theoretical and a numerical point of view. Particular attention has been paid to the wave that is generated at the location of the bed discontinuity. Starting from the classical Shallow Water Equations, considering the bed level as an additional variable, and adding to the system an equation imposing its time invariance, we show that this wave is a contact wave, across which one of the Riemann invariants, namely the energy, is not constant. This is due to the fact that the relevant problem is nonconservative. We demonstrate that, in this type of system, Riemann Invariants do not generally hold in contact waves. Furthermore, we show that in this case the equations that link the flow variables across the contact wave are the Generalized Rankine–Hugoniot relations and we obtain these for the specific problem. From the numerical point of view, we present an accurate and efficient solver for the step Riemann Problem to be used in a finite-volume Godunov-type framework. Through a two-step predictor–corrector procedure, the solver is able to provide solutions with any desired accuracy. The predictor step uses a well-balanced Generalized Roe solver while the corrector step solves the exact nonlinear system of equations that consitutes the problem by means of an iterative procedure that starts from the predictor solution. In order to show the effectiveness and the accuracy of the proposed approach, we consider several step Riemann Problems and compare the exact solutions with the numerical results obtained by using a standard Roe approach far from the step and the novel two-step algorithm for the fluxes over the step, achieving good results.     

On multidimensional ultrasonic scattering in an inhomogeneous elastic background.

This work is concerned with the modeling of elastic wave scattering by solid or fluid-filled objects embedded in an inhomogeneous elastic background. The medium is probed by a monochromatic force and the scattered field is computed (forward problem) or observed (inverse problem) at some known receiver locations. Based on vector integral equations for elastic scattering, a general framework is developed, independent of both the problem geometry and the transmitter-receiver characteristics. This framework encompasses both forward and inverse modeling. In the forward model, a Born approximation for an inhomogeneous background is applied to obtain a closed form expression for the scattered field. In the inverse model, this approximation is also invoked to linearize for the multiparameter characteristic of the object. Finally, an iterative inversion scheme alternating forward and inverse modeling is proposed to improve the resolution and accuracy of the reconstruction algorithm.     

A high-order accurate unstructured finite volume Newton–Krylov algorithm for inviscid compressible flows

A fast implicit Newton–Krylov finite volume algorithm has been developed for high-order unstructured steady-state computation of inviscid compressible flows. The matrix-free generalized minimal residual (GMRES) algorithm is used for solving the linear system arising from implicit discretization of the governing equations, avoiding expensive and complex explicit computation of the high-order Jacobian matrix. The solution process has been divided into two phases: start-up and Newton iterations. In the start-up phase an approximate solution with the general characteristics of the steady-state flow is computed by using a defect correction procedure. At the end of the start-up phase, the linearization of the flow field is accurate enough for steady-state solution, and a quasi-Newton method is used, with an infinite time step and very rapid convergence. A proper limiter implementation for efficient convergence of the high-order discretization is discussed and a new formula for limiting the high-order terms of the reconstruction polynomial is introduced. The accuracy, fast convergence and robustness of the proposed high-order unstructured Newton–Krylov solver for different speed regimes is demonstrated for the second, third and fourth-order discretization. The possibility of reducing computational cost required for a given level of accuracy by using high-order discretization is examined.     

An Implicit Scheme for Nonideal Magnetohydrodynamics

A new implicit algorithm is developed for solving the time-dependent, nonideal magnetohydrodynamic equations. It can also be used as an efficient relaxation scheme for steady state solutions. The algorithm is a finite-volume scheme that uses an approximate Riemann solver for the hyperbolic fluxes and central differencing applied on nested control volumes for the parabolic fluxes that arise from the non-ideal terms (i.e., resistivity and viscosity). In one dimension the scheme is second-order accurate in space and time. In two or three dimensions, the accuracy is between first and second order. For the class of problems considered, the implicit formulation is stable for any size time step, thus allowing efficient tracking of slower transients. The implicit operator is inverted using a lower–upper symmetric Gauss–Seidel iteration. Results from several test cases are presented that show good agreement with analytical solutions and illustrate the advantages of the scheme.     

A dispersion-relation-preserving algorithm for a nonlinear shallow-water wave equation

The paper presents an iterative algorithm for studying a nonlinear shallow-water wave equation. The equation is written as an evolution equation, involving only first-order spatial derivatives, coupled with the Helmholtz equation. We propose a two-step iterative method that first solves the evolution equation by the implicit midpoint rule and then solves the Helmholtz equation using a three-point sixth-order compact scheme. The first-order derivative terms in the first step are approximated by a sixth-order dispersion-relation-preserving scheme that preserves the physically inherent dispersive nature. The compact Helmholtz solver, on the other hand, allows us to use relatively few nodal points in a stencil, while achieving a higher-order accuracy. The midpoint rule is a symplectic time integrator for Hamiltonian systems, which may be a preferable method to solve the spatially discretized evolution equation. To give an assessment of the dispersion-preserving scheme, we provide a detailed analysis of the dispersive and dissipative errors of this algorithm. Via a variety of examples, we illustrate the efficiency and accuracy of the proposed scheme by examining the errors in different norms and providing the rates of convergence of the method. In addition, we provide several examples to demonstrate that the conserved quantities of the equation are well preserved by the implicit midpoint time integrator. Finally, we compare the accuracy, elapsed computing time, and spatial and temporal rates of convergence among the proposed method, a complete integrable particle method, and the local discontinuous Galerkin method.     

Reconstruction of the fine structure of an acoustic scatterer against the distorting influence of its large-scale inhomogeneities

In the ultrasonic diagnostics of small-size neoplasms of biological tissues at the earliest stage of their development, an efficient way to eliminate the distorting influence of high-contrast or large inhomogeneities of the biological medium is to apply the iterative technique. A simple approach is proposed, which makes it possible with only two iteration steps to achieve an efficient focusing of the tomograph array. At the first step, the unknown distribution of the large-scale inhomogeneities of sound velocity and absorption over the scatterer is reconstructed, where the large-scale inhomogeneities are those whose size exceeds several wavelengths. At the second step, the fine structure of the scatterer is reconstructed against the large-scale background, which can be performed with a high accuracy owing to the evaluation of the background at the first step. The possibility of simultaneous reconstruction of the large-scale and fine structures by the noniterative Grinevich-Novikov algorithm is considered as an alternative. This algorithm reconstructs in an explicit form two-dimensional refractive-absorbing acoustic scatterers of almost arbitrary shape and strength. Taking into account the effects of multiple scattering, this algorithm provides resolution of the fine structure almost as good as that achieved in reconstructing the same structure against an undistorting homogeneous background. The results of numerical simulations of both algorithms are presented.     

Importance of the (nabla) D term in frequency-resolved optical diffusion imaging

The effects of the approximation DD=0 that is often used in frequency-resolved optical diffusion imaging are examined. It is shown that this approximation can affect the performance of integral-equation-based approaches to optical diffusion imaging, such as the Born iterative method and the distorted Born iterative method. The approximation introduces errors into the calculation of data used in simulations, which can lead to misleading evaluations of reconstruction algorithms. Numerical calculations show the magnitude of these effects and the appearance of artifacts in reconstructed images when conventional inversion algorithms are applied to more accurately calculated data.     

An efficient multi-scale Poisson solver for the incompressible Navier–Stokes equations with immersed boundaries

The iterative-multi-scale-finite-volume (IMSFV) procedure is applied as an efficient solver for the pressure Poisson equation arising in numerical methods for the simulation of incompressible flows with the immersed-interface method (IIM). Motivated by the requirements of the specific IIM implementation, a modified version of the IMSFV algorithm is presented to allow the solution of problems, in which the varying coefficient of the elliptic equation (e.g. the permeability of the medium in the context of the simulation of flows in porous media) varies over several orders of magnitude or even becomes zero within the integration domain. Furthermore, a strategy is proposed to incorporate the iterative procedure needed by the IIM to converge out constraints at immersed boundaries into the iterative IMSFV cycle. No significant deterioration of performance of the IMSFV method is observed with respect to cases, in which no iterative improvement of the boundary conditions is considered.     

水平层状横向同性地层中频率测深资料全参数快速迭代反演

提出水平层状横向同性地层中频率测深资料的全参数快速迭代反演算法,以便从测量资料中同时确定各个地层的横向、 纵向电导率及层界面深度.首先,利用水平层状介质中电磁场并矢Green函数在频率波数域中的解析解和Sommerfeld积分的 快速计算技术确定正演响应.然后,利用摄动理论和Fourier逆变换公式,研究建立一套快速求解全参数Fréchet导数的 有效算法,并利用规范化处理和奇异值分解技术给出迭代反演过程.最后,给出数值试验证明反演理论的有效性以及反演算法 的抗噪声能力.     

基于结构字典学习的图像复原方法

本文提出一种新的结构字典学习方法,并利用它进行图像复原。首先给出结构字典学习的基本内容和方法,然后将傅里叶正则化方法和结构字典学习方法有效整合到图像复原算法中。结构字典学习方法是先将原图像进行结构分解,再分别学习出每个结构图像中的字典,最后利用这些字典对原图像进行稀疏的表示。结合傅里叶正则化,提出了一种有效的迭代图像复原算法:第一步在傅里叶域利用正则化反卷积方法得到图像的初步估计;第二步采用结构字典学习的方法对遗留的噪声进行去噪处理。实验结果表明,提出的方法在改进信噪比和视觉质量上都要优于6种先进的图像复原方法,改进的信噪比平均提升0.5 d B以上。     

基于自适应差分进化算法的阵列侧向测井快速反演

严格意义上的电测井反演在每一次反演算法迭代过程中都要进行多次正演计算,耗时长,在复杂三维地层模型中电测井数据的实时反演不太可能实现,对现场实时高效处理电测井数据提出了挑战.本文基于径向阶跃介质模型,预先计算正演响应,在反演过程中直接进行线性插值调用,大大节省反演时间.提出一种自适应差分进化算法,将阵列侧向反演问题转化为一种非线性的全局优化问题,通过与经典差分进化算法、马奎特算法进行比较,自适应差分进化算法具备寻优成功率高（90%）、平均迭代次数少（21）、抗噪性好的特点.利用不同侵入条件下的层状介质模型进行算法验证,结果表明改进算法反演的电阻率较视电阻率更加接近储层真实电阻率,可以满足油气藏评价的需要.     

Inverse problem of the wave equation and the Schwinger approximation

A new method of profile inversion for acoustic waves propagating in a medium with spherical inhomogeneity based on the Schwinger variational method is presented. The wave equation of interest is transformed into a Schrodinger equation, so that the Born approximation and the new method could also be applied at high frequencies. It is shown that the new method is stable and is more accurate than the Born approximation. To illustrate the method, an exactly solvable analytical example is presented. Also numerical examples using synthetic data, with and without additive noise, are given and the corresponding inversion results and the stability of the method are studied.     

一种基于激光辐照热效应的薄膜参数反演方法

本文研究并建立了一种基于激光辐照热效应的薄膜参数反演方法.首先给出激光辐照薄膜产生温升问题的热传导理论模型,并利用拉普拉斯变换得到了膜层和基底温度场的解析解;然后以膜层和基底的导热系数为反演参数,基于非线性共轭梯度算法给出反演基本原理及流程,并推导得到了反演过程中灵敏度系数的解析表达式;以aluminum,silver,copper和gold四种金属薄膜为例,通过与有限元法的计算结果对比验证了温度场解析解的正确性;最后结合四种金属薄膜进行了参数反演,通过考察分析不同随机噪声等条件下的参数反演结果,验证了本文方法在薄膜参数反演精度与反演效率等方面的有效性.反演结果显示:本文方法具有较高的反演精度和效率,在迭代截止误差为10~(-7)时只需用少于20次迭代就能收敛;在测量数据中加入的随机噪声越小,反演的迭代收敛次数就越少,即使是在迭代初值与反演结果相差较大时,用包含5%随机噪声的测量数据反演也能快速收敛.本文提出的薄膜参数反演方法不仅适用于反演导热系数,也可扩展用于反演膜层反射系数或吸收率等参数,具有一定的适用性.本文方法对于激光加工或激光损伤过程中的参数反演及优化具有一定的指导意义.     

Event-based parareal: A data-flow based implementation of parareal

Parareal is an iterative algorithm that, in effect, achieves temporal decomposition for a time-dependent system of differential or partial differential equations. A solution is obtained in a shorter wall-clock time, but at the expense of increased compute cycles. The algorithm combines a fine solver that solves the system to acceptable accuracy with an approximate coarse solver. The critical task for the successful implementation of parareal on any system is the development of a coarse solver that leads to convergence in a small number of iterations compared to the number of time slices in the full time interval, and is, at the same time, much faster than the fine solver. Very fast coarse solvers may not lead to sufficiently rapid convergence, and slow coarse solvers may not lead to significant gains even if the number of iterations to convergence is satisfactory. We find that the difficulty of meeting these conflicting demands can be substantially eased by using a data-driven, event-based implementation of parareal. As a result, tasks for one iteration do not wait for the previous iteration to complete, but are started when the needed data are available. For given convergence properties, the event-based approach relaxes the speed requirements on the coarse solver by a factor of ～K, where K is the number of iterations required for a converged solution. This may, for many problems, lead to an efficient parareal implementation that would otherwise not be possible or would require substantial coarse solver development. In addition, the framework used for this implementation executes a task when the data dependencies are satisfied and computational resources are available. This leads to improved computational efficiency over previous approaches that pipeline or schedule groups of tasks to a particular processor or group of processors.     

基于多时相TanDEM-X极化干涉SAR数据的水稻株高反演

水稻株高是水稻本身以及土壤、水文、气象等因素的综合反映,是水稻长势监测的重要指标。准确、高效、大范围的株高反演为水稻品种识别、物候监测、病虫害评估和产量预测等提供了可靠的依据。合成孔径雷达(SAR),具有全天时、全天候、穿透性的优势,成为水稻株高反演的重要手段之一。基于极化干涉测量(PolInSAR)的散射模型的反演算法具有严密的物理模型的支撑及较高的反演精度等特点,成为植被高度反演研究的热点。结合极化干涉SAR技术,构建了一种基于RVoG(Random Volume over Ground)模型的水稻株高反演算法,并利用2015年水稻生长季内9个时相的TanDEM-X极化干涉SAR数据,进行了水稻株高反演试验。首先基于每个时相下的极化干涉SAR数据分别得到8个复相干系数,利用这8个复相干系数在考虑卫星双站模式等情况下进行去相干处理,然后建立适用于水稻田特性的RVoG模型,接着构建基于该模型的水稻株高反演迭代算法,最后对9个时相下的TanDEM-X数据进行研究区的水稻株高反演及精度评定。结果表明,当水稻株高高于0.4m时,该方法的反演结果较好,决定系数(R^2)为0.86,均方根误差RMSE为6.79 cm;当水稻株高较低时(水稻株高小于0.4 m),反演误差在0.1~0.8 m之间,反演结果较差,被明显高估。通过分析认为,基于极化干涉理论,TanDEM-X数据在较好地反映出水稻植株的较大体散射量的前提下,利用所构建的基于RVOG模型的水稻株高反演算法,能够较好地反演株高在0.33~1.2 m的水稻株高。