Intelligent interactive multiobjective optimization method and its application to reliability optimization

In most practical situations involving reliability optimization, there are several mutually conflicting goals such as maximizing the system reliability and minimizing the cost, weight and volume. This paper develops an effective multiobjective optimization method, the Intelligent Interactive Multiobjective Optimization Method (IIMOM). In IIMOM, the general concept of the model parameter vector is proposed. From a practical point of view, a designer's preference structure model is built using Artificial Neural Networks (ANNs) with the model parameter vector as the input and the preference information articulated by the designer over representative samples from the Pareto frontier as the desired output. Then with the ANN model of the designer's preference structure as the objective, an optimization problem is solved to search for improved solutions and guide the interactive optimization process intelligently. IIMOM is applied to the reliability optimization problem of a multi-stage mixed system with five different value functions simulating the designer in the solution evaluation process. The results illustrate that IIMOM is effective in capturing different kinds of preference structures of the designer, and it provides a complete and effective solution for medium- and small-scale multiobjective optimization problems.     

Controlling first four moments for robust optimization

The paper addresses the solution of robust moment-based optimization problems after a multipoint reformulation. The first four moments are considered (i.e. mean, variance, skewness and kurtosis) going beyond classical engineering optimization based on the control of the mean and variance . In particular, the impact on the design of a control of the third and fourth moments are discussed. The multipoint formulation leads to discrete expressions for the moments. linking moment-based and multipoint optimizations. The linearity of the sums in the discrete moments permits an easy evaluation of their gradients with respect to the design variables. Optimal sampling issues are analyzed and a procedure is proposed to quantify the confidence level on the robustness of the design. The proposed formulation is fully parallel and the time-to-solution is comparable to single-point situations. It is applied to three problems: an analytical least-square minimization problem, a shape optimization problem with a reduced-order model, and a full aircraft shape optimization robust over a range of transverse winds.     

基于矩量法的移动荷载识别

从桥梁响应识别桥面移动荷载往往出现逆问题的病态（不适定性）等共性问题。本文基于移动荷载识别理论，借助矩量法求解积分方程理论并采用整域基函数——正交勒让德多项式表达桥面移动荷载，提出了一种移动荷载识别的时域改进算法。两轴车辆多种组合工况下的常载和时变荷载数值仿真研究表明：与时域法比较，改进时域法识别桥面移动荷载时，其识别精度高、抗噪能力强，识别结果不适定性有显著改善。     

基于线性不变矩和角度向量的立体匹配算法

针对室内场景双目立体匹配有别于一般场景立体匹配的特殊性,提出了一种计算简便、准确度高的立体图像匹配算法.该算法首先利用canny算子检测物体的边缘,根据边缘的线性不变矩寻找出目标物体,然后提取出目标物体轮廓的特征点,利用角度直方图计算出左右图像的旋转角度,最后利用角度向量实现左右图像的对应像素点的匹配.线性不变矩有效地将计算复杂度由二维降低到一维,大大降低了计算量.角度向量的提出降低了特征点匹配的复杂度,而且计算简便,准确率高.实验表明,该算法对图像的缩放、旋转、平移均免疫,具有较高的识别精度和良好的抗干扰性,计算效率高于传统方法,有着较高的应用价值.     

A variant space search method and its application to the optimization design of compressor profiles

Optimization methods have been widely used in practical engineering, with search efficiency and global search ability being the main evaluation criteria. In this article, the Bezier curve equivalent recursion is used in a genetic algorithm (GA) to realize the variant space search to improve the search efficiency and global search ability. The parameters related to this method are investigated by an optimization test of the simple curve approximation, which is then used for optimization designs of supersonic and transonic profiles. The results show that the GA can be improved if the variant space search method is added.     

The structures and magnetic moments of Co-C clusters

The geometries, binding energies, and magnetic moments of small CoC(N) (N = 1-8) and CO2C(N) (N = 1-6) clusters are studied systematically using all-electron density functional theory (DFT) with the generalized gradient approximation (GGA). The results indicate that, for the CoC(N) (N = 1-8) and Co2C(N) (N = 1-6) clusters, the lowest-energy structures are predicted to be linear structures except for CoC2 and CoC7. The ground states of the CoC(N) (N = 1-8) clusters are linear geometries (C(v)) with Co atom at one end. The ground states of the Co2C(N) (N = 1-6) clusters are linear geometries (D(h)) with the two Co atoms located at the two ends. For all the clusters, analysis of the Mülliken population shows that charge transfers from the Co atom(s) to the C atoms. The magnetic moment lies primarily on the Co atom(s).     

The method of moving asymptotes—a new method for structural optimization

A new method for non-linear programming in general and structural optimization in particular is presented. In each step of the iterative process, a strictly convex approximating subproblem is generated and solved. The generation of these subproblems is controlled by so called ‘moving asymptotes’, which may both stabilize and speed up the convergence of the general process.     

Structural shape optimization with meshless method and swarm-intelligence based optimization

International Journal of Mechanics and Materials in Design - This paper presents a distinctive numerical approach for shape optimization by coupling meshless method with stochastic swarm...     

Recognition of motion-blurred images by use of the method of moments

Image motion causes a blur that changes features of objects and therefore complicates the task of automatic recognition. In this work we develop two recognition methods for motion-blurred images. For the first method we assume that the motion function and direction during the exposure are given. We develop the relation between the blurred-image moments and the original-image moments based on the motion function only. The recognition is carried out by comparing the moments of the restored image against the moments of the image database. In the second method the motion function is not known. In this case image moments that are invariant with respect to the motion blur are identified, and only these moments are used for recognition. The advantage of the suggested methods is that no time-consuming image restoration is required prior to recognition.     

Justification of the method of moments in the theory of diffraction

Questions related to justification of the method of moments are considered. It is shown that the structure of many equations of the theory of diffraction ensures convergence of the approximated solutions to exact ones. The operators of the diffraction problems can be presented as the sums of a positive operator and a completely continuous operator.     

The residual variable method and its applications

Summary We consider a partial differential equation in spherical coordinates which describes a dynamic process going on in an infinite medium with an inner spherical boundary. If an analytical solution to the problem is not possible to obtain then one would have to resort to numerical techniques. It becomes necessary to discretize the infinite domain even if the solution is required on the inner spherical surface only. The numerical difficulties associated with the discretization of an infinite medium are well known. The Residual Variable Method (RVM) is a rigorous method which essentially reduces the number of the spatial dimensions of the problem by one. The governing differential equation is integrated once in the radial direction and, thus, it becomes possible to determine the solution on the inner boundary without having to deal with the infinite domain. The applications of the RVM to the wave equations in acoustic and viscous media and to the diffusion equation are shown.With 4 Figures     

Quantitative analysis of magnetic resonance radio-frequency coilsbased on method of moments

To investigate both spectral and spatial domain characteristics of radio-frequency coils in magnetic resonance experiments, we have developed a new approach based on the method of moments. Instead of the conventional point-matching scheme, the loop testing function is used. Such a testing function decreases the complexity of computation and elevates the efficiency of simulation. With the proposed testing function incorporated with a pulse basis function based on coil geometry topology, performance of both surface coil and volume coil can be predicted with consistent results compared with experimental data     

An efficient auxiliary projection-based multigrid isogeometric reanalysis method and its application in an optimization framework

An efficient optimization framework is developed in this study by integrating auxiliary projection-based multigrid isogeometric reanalysis (MG-IGR) and metaheuristic searching techniques. It is well known that the inherent characteristics of isogeometric analysis (IGA) are superior in shape optimization problems. Inheriting the characteristics of IGA, an auxiliary projection-based MG reanalysis (MGR) is proposed to construct mapping between the mesh before modification and after modification during the optimization process. Subsequently, MG-IGR is utilized to reanalyze the modified design efficiently by reusing the initial evaluated results. Moreover, the proposed MG-IGR also eliminates the restriction of mesh consistency. In this framework, the structure can be designed directly through parameterized control of the non-uniform rational B-spline (NURBS) model, and the MG-IGR fast solver enables any metaheuristic algorithm to perform the optimization procedure. Moreover, the accuracy of the simulation can be guaranteed by the NURBS model and the convergence criterion of the MG. Finally, two geometric optimization examples are presented to validate the performance of the developed framework.     

A fixed‐grid bidirectional evolutionary structural optimization method and its applications in tunnelling engineering

Topology optimization has exhibited an exceptional capability of improving structural design. However, several typical topology optimization algorithms are finite element (FE) based, where mesh‐dependent zigzag representation of boundaries is barely avoidable in both intermediate and final results. To tackle the problem, this paper proposes a new fixed‐grid‐based bidirectional evolutionary structural optimization method, namely FG BESO. The adoption of an FG FE framework enables a continuous boundary change in the course of topology optimization, which provides a means of dealing with not only the non‐smooth boundary of the final design but also the interpretation of intermediate densities. As a class of important practical application, it is interesting to make use of the new FG BESO method to the reinforcement design for underground tunnels. To accommodate the FG BESO technique to geological engineering applications, a nodal sensitivity is derived for a two‐phase material model comprising the artificial reinforcement and original rock. In this paper, some innovative topological designs of tunnel reinforcements are presented for minimizing the floor and sidewall heaves under different geological loading conditions. Copyright © 2007 John Wiley & Sons, Ltd.     

Electromagnetic analysis of axially symmetric diffractive lenses with the method of moments

We present the electromagnetic analysis of axially symmetric diffractive lenses. Analysis is performed by numerically solving the electric and magnetic field integral equations using the method of moments, and it exploits axial symmetry to reduce computational cost. Formulations for the analysis of loss less dielectric and perfectly conducting lenses are presented. The analysis of binary and eight-level lenses are performed to illustrate the utility of the technique.