A parallel adaptive mesh approach for flowfields with shock waves

A simple and efficient implementation of Adaptive Mesh Refinement (AMR) with distributed-memory approach is presented. Introducing a lookup table including grid connectivity information and simplified algorithms for AMR, the procedures for reconstructing adaptive grids are carried out in parallel, with local data to a large extent. A simple static load-balancing scheme is adopted, and the grids are not repartitioned and no data redistribution is performed. A numerical example on two different parallel computers shows that the proposed implementation of AMR is effective to reduce the computational time for unsteady flows with shock waves. Received 23 October 2000 / Accepted 30 March 2001 Published online 11 June 2002     

带有未知非对称控制增益的不确定分数阶混沌系统自适应模糊同步控制

针对带有非对称控制增益的不确定分数阶混沌系统的同步问题设计了模糊自适应控制器. 模糊逻辑系统用来逼近未知的非线性函数, 非对称的控制增益矩阵被分解为一个未知的正定矩阵、一个对角线上元素为+1或-1的已知对角矩阵和 一个未知的上三角矩阵的乘积. 基于分数阶Lyapunov稳定性理论构造了模糊控制器以及分数阶的参数自适应律, 在保证所有变量有界的情况下实现驱动系统和响应系统的同步. 在分数阶系统稳定性分析中给出了一种平方Lyapunov函数的使用方法, 根据此方法很多针对整数阶系统的控制方法可以推广到分数阶系统中. 最后数值仿真结果验证了所提控制方法的可行性.     

Comparison of adjoint‐based and feature‐based grid adaptation for functional outputs

Adjoint‐based and feature‐based grid adaptive strategies are compared for their robustness and effectiveness in improving the accuracy of functional outputs such as lift and drag coefficients. The output‐based adjoint approach strives to improve the adjoint error estimates that relate the local residual errors to the global error in an output function via adjoint variables as weight functions. A conservative adaptive indicator that takes into account the residual errors in both the primal (flow) and dual (adjoint) solutions is implemented for the adjoint approach. The physics‐based feature approach strives to identify and resolve significant features of the flow to improve functional accuracy. Adaptive indicators that represent expansions and compressions in the flow direction and gradients normal to the flow direction are implemented for the feature approach. The adaptive approaches are compared for functional outputs of three‐dimensional arbitrary Mach number flow simulations on mixed‐element unstructured meshes. Grid adaptation is performed with h‐refinement and results are presented for inviscid, laminar and turbulent flows. Copyright © 2006 John Wiley & Sons, Ltd.     

面向多部门多属性的群决策应急方案调整方法

针对具有多部门多属性的基于案例推理的应急方案生成问题,提出了一种新的群决策应急方案调整方法。首先,各部门根据关注的属性生成案例库,并应用检索方法得到最相似历史案例,再运用置信规则库进行应急方案调整来生成各部门应急方案;然后,各部门对每个部门生成的应急方案进行评价;在此基础上,根据各部门的评价信息确定权重,进而对各部门生成的应急方案进行集结得到目标案例的应急方案。最后,通过一个算例验证了所提出方法的可行性和有效性。     

REVIEW: High pressure NMR study of proteins – seeking roots for function,evolution, disease and food applications

NMR experiments at variable pressure reveal a wide range of conformation of a globular protein spanning from within the folded ensemble to the fully unfolded ensemble, herewith collectively called “high-energy conformers”. The observation of “high-energy conformers” in a wide variety of globular proteins has led to the “volume theorem”: the partial molar volume of a protein decreases with the decrease in its conformational order. Since “high-energy conformers” are intrinsically more reactive than the basic folded conformer, they could play decisive roles in all phenomena of proteins, namely function, environmental adaptation and misfolding. Based on the information on high-energy conformers and the rules on their partial volume in its monomeric state and amyloidosis, one may have a general view on what is happening on proteins under pressure. Moreover, one may even choose a high-energy conformer of a protein with pressure as variable for a particular purpose. Bridging “high-energy conformers” to macroscopic pressure effects could be a key to success in pressure application to biology, medicine, food technology and industry in the near future.     

Measuring the fuzziness of human thoughts: An application of fuzzy sets to sociological research

Conventionally, sociologists measure the membership of an individual to a group by a “0 or 1” characteristic function. But when the definition of that group is fuzzy and an individual is neither a full member nor a nonmember, this dichotomous characteristic function may distort the reality. Instead of the “0 or 1” characteristic function by classical set theory, fuzzy set theory introduces a membership function which is a gradation from 0 to 1 to measure the degree to which an object (an individual) belongs to a concept (a group). Based on the rationale of fuzzy set theory, we suggest some new methods of data collection and analysis. Among several noteworthy findings, two points are emphasized: 1) the fuzzy set is an appropriate way of measuring the fuzziness of human thought; and 2) it allows one to relax the conventional assumption that all individuals have identical distributions and deviations around their means.     

Supervised Domain Adaptation for Automated Semantic Segmentation of the Atrial Cavity

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria. For this, there is an interest in automatic image segmentation algorithms, such as deep learning (DL) methods, as opposed to manual segmentation, an error-prone and time-consuming method. However, to optimize DL algorithms, many annotated examples are required, increasing acquisition costs. The aim of this work is to develop automatic and high-performance computational models for left and right atrium (LA and RA) segmentation from a few labelled MRI volumetric images with a 3D Dual U-Net algorithm. For this, a supervised domain adaptation (SDA) method is introduced to infer knowledge from late gadolinium enhanced (LGE) MRI volumetric training samples (80 LA annotated samples) to a network trained with balanced steady-state free precession (bSSFP) MR images of limited number of annotations (19 RA and LA annotated samples). The resulting knowledge-transferred model SDA outperformed the same network trained from scratch in both RA (Dice equals 0.9160) and LA (Dice equals 0.8813) segmentation tasks.     

数字图像一阶矩的自动聚焦区域选择算法

聚焦区域选择是自动聚焦算法中的重要模块,直接影响评价函数曲线的尖锐性、准确性和稳定性。针对中心取窗和多点取窗等传统聚焦区域选择算法的局限性,提出了一种基于数字图像一阶矩的自动聚焦区域选择算法,它是通过图像灰度或边缘一阶矩定位聚焦区域的。传统聚焦区域选择是一种定点估计,实验证明一阶矩方式选择可以跟踪偏离中心的主体景物,是一种具有自适应性的前景位置估计算法,提高了聚焦精确度和速度。     

Nonlinear corrector for Reynolds-averaged Navier-Stokes equations

The scope of this paper is to present a nonlinear error estimation and correction for Navier-Stokes and Reynolds-averaged Navier-Stokes equations. This nonlinear corrector enables better solution or functional output predictions at fixed mesh complexity and can be considered in a mesh adaptation process. After solving the problem at hand, a corrected solution is obtained by solving again the problem with an added source term. This source term is deduced from the evaluation of the residual of the numerical solution interpolated on the h/2 mesh. To avoid the generation of the h/2 mesh (which is prohibitive for realistic applications), the residual at each vertex is computed by local refinement only in the neighborhood of the considered vertex. One of the main feature of this approach is that it automatically takes into account all the properties of the considered numerical method. The numerical examples point out that it successfully improves solution predictions and yields a sharp estimate of the numerical error. Moreover, we demonstrate the superiority of the nonlinear corrector with respect to linear corrector that can be found in the literature.     

A study of properties of adaptive quadratic grids for three-dimensional near-surface field computations

Curved geometries and the corresponding near-surface fields typically require a large number of linear computational elements. High-order numerical solvers have been primarily used with low-order meshes. There is a need for curved, high-order computational elements. Typical near-surface meshes consist of hexahedral and/or prismatic elements. The present work studies the employment of quadratic meshes that are relatively coarse for field simulations. Directionally quadratic high-order elements are proposed for the near-surface field regions. The quadratic meshes are compared with the conventional low-order ones in terms of accuracy and efficiency. The cases considered include closed surface volume calculations, as well as computation of gradients of several analytic fields. A special method of adaptive local quadratic meshes is proposed and evaluated. Truncation error analysis for quadratic grids yields comparison with the conventional linear hexahedral/prismatic meshes, which are subject to typical distortions such as stretching, skewness, and torsion.