An arbitrary order variationally consistent integration for Galerkin meshfree methods

Because most approximation functions employed in meshfree methods are rational functions with overlapping supports, sufficiently accurate domain integration becomes costly, whereas insufficient accuracy in the domain integration leads to suboptimal convergence. In this paper, we show that it is possible to achieve optimal convergence by enforcing variational consistency between the domain integration and the test functions, and optimal convergence can be achieved with much less computational cost than using higher‐order quadrature rules. In fact, stabilized conforming nodal integration is variationally consistent, whereas Gauss integration and nodal integration are not. In this work the consistency conditions for arbitrary order exactness in the Galerkin approximation are set forth explicitly. The test functions are then constructed to be variationally consistent with the integration scheme up to a desired order. Attempts are also made to correct methods that are variationally inconsistent via modification of test functions, and several variationally consistent methods are derived under a unified framework. It is demonstrated that the solution errors of PDEs due to quadrature inaccuracy can be significantly reduced when the variationally inconsistent methods are corrected with the proposed method, and consequently the optimal convergence rate can be either partially or fully restored. Copyright © 2013 John Wiley & Sons, Ltd.     

A New Decision-Making Model Based on Plithogenic Set for Supplier Selection

Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability. The choice of supplier is a multi-criteria decision making (MCDM) to obtain the optimal decision based on a group of criteria. The health care sector faces several types of problems, and one of the most important is selecting an appropriate supplier that fits the desired performance level. The development of service/product quality in health care facilities in a country will improve the quality of the life of its population. This paper proposes an integrated multi-attribute border approximation area comparison (MABAC) based on the best-worst method (BWM), plithogenic set, and rough numbers. BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency. For the treatment of uncertainty, a plithogenic set and rough number (RN) are used to improve the accuracy of results. Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness. Then, based on the plithogenic aggregation and the results of BWM evaluation, we use MABAC to find the optimal alternative according to defined criteria. To examine the proposed integrated algorithm, an empirical example is produced to select an optimal supplier within five options in the healthcare industry.     

基于逆系统方法的航天器姿态跟踪最优鲁棒控制

针对航天器有效载荷(如星载天线、星载相机)快速持续指向地面或在轨特定目标等空间任务,研究了航天器姿态快速连续跟踪控制问题。提出了一种计算跟踪参考姿态的新方法,给出了目标姿态参数的解析表达式。大范围机动时,姿态动力学方程是强耦合非线性的,用传统鲁棒控制方法处理比较困难。用机动四元数描述姿态误差,以避免姿态跟踪可能产生的奇异。在考虑参数不确定性和干扰力矩的情况下,应用逆系统方法和输入不确定性鲁棒控制与最优控制转换定理,将鲁棒控制问题转化为最优控制问题,回避了传统鲁棒控制复杂的设计过程。控制器的设计方法简单,可应用于更复杂的对象,且参数选择具有很大的灵活性,易于工程实现。仿真结果表明:控制器具有良好的鲁棒性,较高的跟踪精度和快速响应能力。     

A discontinuous and adaptive reduced order model for the angular discretization of the Boltzmann transport equation

This article presents a new adaptive reduced order model for resolving the angular direction of the Boltzmann transport equation, based on proper orthogonal decomposition (POD) and the method of snapshots. It builds upon previous methods of applying POD to the angular dimension, with modifications to increase accuracy and solver stability. Previous methods used continuous global functions spanning the whole sphere. The new approach, discontinuous POD (DPOD), partitions the surface of the sphere into angular regions, each with an independent set of POD basis functions. Combined, these can approximate flux distributions which span the sphere using optimized basis functions for each angular region. In addition, a novel implementation of adaptive angular resolution known as adaptive discontinuous POD (ADPOD) is presented, which allows the number of DPOD basis functions to vary by angular octant and spatial element. DPOD and ADPOD are applied to two problems in order to demonstrate their benefits compared with POD. Both are shown to reduce the number of solver iterations required to find a solution and decrease the error in the angular flux.     

Axial and angular displacement fiber-optic sensor

An intensity-based fiber-optic sensor for measuring axial and angular displacement has been designed and tested in a controlled laboratory environment. In addition, a mathematical model allowing the simultaneous calculation of the three desired parameters needed to characterize the tilt and the position of a surface under investigation is described. Preliminary tests show good agreement between the theory and the experimental results and show the sensor's potential for application in the manufacturing industry for position and vibration control. The sensor shows significant improvement in angular range over previously reported methods. An axial displacement range of 2 mm, with an accuracy of 40 mum, and an angular displacement range of 40 mrad, with an accuracy of 0.5 mrad, are demonstrated. Suggestions for further improvement of the range and the sensitivity of the sensor are also described.     

Method of Constructing a High-Precision Two-Circuit Angle Measuring System Based on the Combination of Estimates

A method is proposed for constructing a two-circuit measuring system which is equivalent to a combined automatic system. The method makes it possible to increase the measurement accuracy by combining estimates and can find wide application in electronic systems for measuring the angular coordinates of flying vehicles.     

Exact combinatorial reliability analysis of dynamic systems with sequence-dependent failures

Many real-life fault-tolerant systems are subjected to sequence-dependent failure behavior, in which the order in which the fault events occur is important to the system reliability. Such systems can be modeled by dynamic fault trees (DFT) with priority-AND (pAND) gates. Existing approaches for the reliability analysis of systems subjected to sequence-dependent failures are typically state-space-based, simulation-based or inclusion-exclusion-based methods. Those methods either suffer from the state-space explosion problem or require long computation time especially when results with high degree of accuracy are desired. In this paper, an analytical method based on sequential binary decision diagrams is proposed. The proposed approach can analyze the exact reliability of non-repairable dynamic systems subjected to the sequence-dependent failure behavior. Also, the proposed approach is combinatorial and is applicable for analyzing systems with any arbitrary component time-to-failure distributions. The application and advantages of the proposed approach are illustrated through analysis of several examples.     

Reliability allocation methods: A systematic literature review

The choice of a reliability allocation method is not always easy or straightforward, since it depends on several factors. Some factors are directly related to the characteristics of the analyzed system, such as the level of complexity or the reliability configuration; on the other hand, additional aspects constitute boundary conditions, such as budget or experimentation time. In this scenario, the purpose of the present research is to present a systematic literature review on reliability allocation, proposing a guideline to choose the optimal allocation method in respect to the desired application, available resources, and required accuracy. The proposed review analyzes allocation methods in literature, determining main features and area of application. Motivated by a lack of a comprehensive methods summarization present in literature, our research goal is to assist practitioners in choosing a well-suited method and to provide an overview, to support academics in conducting new research in this area. The results of the performed analysis are synthetized according to several criteria. The results are summarized and categorized in different clusters for each individuated application field. The proposed summarization design allows an easy and rapid consultation.     

Angular velocity estimation from measurement vectors of star tracker

In most spacecraft, there is a need to know the craft's angular rate. Approaches with least squares and an adaptive Kalman filter are proposed for estimating the angular rate directly from the star tracker measurements. In these approaches, only knowledge of the vector measurements and sampling interval is required. The designed adaptive Kalman filter can filter out noise without information of the dynamic model and inertia dyadic. To verify the proposed estimation approaches, simulations based on the orbit data of the challenging minisatellite payload (CHAMP) satellite and experimental tests with night-sky observation are performed. Both the simulations and experimental testing results have demonstrated that the proposed approach performs well in terms of accuracy, robustness, and performance.     

Multiparameter optimization of inverse filtering algorithms

This paper investigates inverse filtering of transient signals. The problem is ill-conditioned, which means that a small uncertainty in the measurement causes large deviations in the reconstructed signal. This amplified noise has to be suppressed at the price of bias in the estimation. The most difficult task is to find the optimal degree of noise reduction. Deconvolution algorithms are usually controlled by one or a few parameters. Several algorithms can be found in the literature to find the best setting of inverse filtering methods; however, usually methods with only one free parameter are handled. In this paper, an algorithm is proposed to optimize several parameters, on the basis of a spectral model. Multiparameter inverse filtering methods have the advantage that they can be better adapted to the measurement system, and to the noise and signal to be measured. The superiority of the proposed optimization method is demonstrated both on simulated and on experimental data     

漂浮基双臂空间机器人基于自适应遗传算法的最优非完整运动规划

讨论了漂浮基双臂空间机器人非完整运动的最优控制规划问题。以多体动力学理论为基础,导出了载体位置、姿态均不受控制情况下,双臂空间机器人耦合了系统动量守恒关系的系统动量矩守恒关系,并将其转化为控制系统状态方程。由此,将双臂空间机器人的非完整运动规划问题转化为非线性系统的控制问题。以此为基础,利用近似优化的方法,给出了双臂空间机器人基于自适应遗传算法的最优非完整运动规划控制算法。其优点在于,仅需要控制双臂空间机器人机械臂的关节运动,即可达到对载体姿态及机械臂关节位置的双重控制效果。一个平面双臂空间机器人系统的数值仿真,验证了算法的有效性。     

Statistically optimised method for detecting adult image groups

Adult image recognition is an important technique for preventing children from accessing offensive material on the Internet. Most of the related works focus on single image recognition. However, adult images usually exist as a group and rarely stand alone. Therefore, considering the entire image group as a whole for classification should be more effective. This paper presents a new method of detecting adult image groups, which aims at achieving optimal recognition accuracy. Adult image group recognition generally includes two components: an adult image recogniser and a final decision rule for classifying the image group. We provide a theoretical analysis to clarify the correlation of the two components and use probability formulae to estimate the recognition rates for different settings of the adult image recogniser and the decision rule. Then, a set of optimal receiver-operating characteristic (ROC) curves for different image numbers is solved. To recognise an unknown image group, a desired recall rate for adult (or benign) image groups is specified and the system is set according to the parameters acquired from the optimal ROC curves. The proposed method can be dynamically adapted to the recall rates that the user expects. This advantage makes the proposed system more suitable for real applications. Our work can be viewed as an extension of single image recognition and the experimental results demonstrate that it can attain higher recognition accuracy than the earlier methods.     

Optimal design and optimal control of structures undergoing finite rotations and elastic deformations

In this work, we deal with the optimal design and optimal control of structures undergoing large rotations and large elastic deformations. In other words, we show how to find the corresponding initial configuration through optimal design or the corresponding set of multiple load parameters through optimal control, in order to recover a desired deformed configuration or some desirable features of the deformed configuration as specified more precisely by the objective or cost function. The model problem chosen to illustrate the proposed optimal design and optimal control methodologies is the one of geometrically exact beam. First, we present a non‐standard formulation of the optimal design and optimal control problems, relying on the method of Lagrange multipliers in order to make the mechanics state variables independent from either design or control variables and thus provide the most general basis for developing the best possible solution procedure. Two different solution procedures are then explored, one based on the diffuse approximation of response function and gradient method and the other one based on genetic algorithm. A number of numerical examples are given in order to illustrate both the advantages and potential drawbacks of each of the presented procedures. Copyright © 2004 John Wiley & Sons, Ltd.     

Optical broadband angular filters based on staggered photonic structures

The potential for use of staggered structures to provide optical broadband angular selectivity is proposed and verified. The numerical results show that the angular selectivity performance characteristics, including the range of the angular-selective region and the full width at half maximum (FWHM) of the angular passband, can be tuned by adjusting the stagger parameter and the number of cells that compose the staggered structure. Therefore, a detailed procedure is given for the design of an angular filter based on a staggered structure with the desired angular-selective region and FWHM. Finally, to confirm the feasibility of fabrication of the designed structures, the error tolerance of this type of angular filter is studied and demonstrated using a statistical method.     

Estimating intravoxel fiber architecture using constrained compressed sensing combined with multitensor adaptive smoothing

In diffusion magnetic resonance imaging (dMRI), the accuracy of fiber tracking and analysis depends directly on that of intravoxel fiber architecture reconstruction. Several methods have been proposed that estimate intravoxel fiber architecture using low angular resolution acquisitions owing to their shorter acquisition time and relatively low b‐values. But these methods are highly sensitive to noise. We propose an approach to estimating intravoxel fiber architecture in low angular resolution dMRI. The method consists in using a constrained compressed sensing (CCS) method, also known as crossing fiber angular resolution of intravoxel architecture (CFARI) technique, in combination with multitensor adaptive smoothing in which a diffusion‐weighted (DW) image smoothing scheme is constructed according to the properties of the multitensor field estimated using CFARI. The results on synthetic, physical phantom and real brain DW images show that the proposed method is able to better resolve fiber architectures while correctly preserving image edge information, which provides a new tool for investigating the microstructures of biological tissues and for fiber tractography. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 285–296, 2015     

基于滑动平均与相关向量机的齿轮早期故障智能诊断

早期故障及时检测与预防维护具有很大的经济与安全意义,提出一种基于相关向量机(RVM)的智能故障诊断方法用于检测齿轮早期故障。首先,小波包变换与Fisher准则结合,自动确定最优分解层次,并在小波包树节点能量中提取出具有最大分类能力的全局最优特征;其次,RVM用于训练故障诊断模型;最后,在线监控过程中,对连续监测的特征值做滑动平均滤波,再输入到故障诊断模型。实验表明,该方法具有很高的分类精度,RVM模型比SVM模型更适合在线故障监测。     

Coupling of element free Galerkin and hybrid boundary element methods using modified variational formulation

 A novel method is proposed by coupling the element free Galerkin (EFG) and the hybrid boundary element (HBE) methods to achieve solution efficiency and accuracy for stress analysis in solids. A modified variational formulation is derived for the present coupled EFG/HBE method so that the continuity and compatibility can be preserved on the interface between the domains of EFG and HBE. The coupled EFG/HBE method has been coded in FORTRAN. The validity and efficiency of the proposed method are demonstrated through a number of example problems. It is found that the present method can take advantages of both EFG and HBE methods. The present method is very easy to implement, and very flexible for obtaining displacements and stresses of desired accuracy in solids, as the efforts for meshing the problem domain have been significantly reduced due to the use of boundary element method (BEM).     

Limit analysis of FRP strengthened masonry arches via nonlinear and linear programming

The collapse load of masonry arches strengthened with FRP materials is determined. The arch is made of quadrangular blocks and the nonlinearity of the problem (no-tension material, frictional sliding and crushing) is concentrated at the interface between the blocks. Two methods are used to solve the problem. In the first method, a nonlinear programming problem (NLP) is formulated and is solved by using the successive quadratic programming algorithm (SQP) and combinatorial analysis. This method finds the optimal solution in the analysed cases. In the second method, a linear programming problem (LP) is formulated and is solved with classical techniques. LP approximates the optimal solution to any desired degree of accuracy. Although the number of variables of LP is much larger than that of NLP, LP process time can result much lower than NLP process time. Numerical examples are provided in order to show the advantages of the two methods and the effectiveness of FRP strengthening for different arch geometries.     

Optimal-control approach to trajectory planning for a class of mobile robotic manipulations

Optimal-control theory is used in the manipulation planning for an ability-limited robot (i.e., a mobile robot with limited maneuverability). The goal of manipulation is to push an object from a given initial configuration to a goal configuration—a common task could be found in the application of mobile robots to manufacturing, in adaptive fixturing for robotic assembly and in robotic gaming. The ability-limited robot is restricted here to perform only two types of motion in a plane. One is pushing the object forward with a constant and fixed velocity, the other one is rotating the object counter-clockwise along a fixed-radius circle with a constant angular velocity. First, the controllability of the proposed manipulation system is proved. Then, the optimal-planning problem is studied within the framework of a switched system. By the aid of optimal-control theory, it is proved that an optimal trajectory involves at most two switchings between these two simple actions. After evaluating the existence and structure of the candidate optimal trajectories, an optimal planner is implemented to find the optimal trajectory. Finally, manipulation examples are provided to demonstrate the proposed manipulation method.