Design and Optimization of Wheel-legged Robot：Rolling-Wolf

Though the studies of wheel-legged robots have achieved great success, the existing ones still have defects in load distribution, structure stability and carrying capacity. For overcoming these shortcomings, a new kind of wheel-legged robot（Rolling-Wolf） is designed. It is actuated by means of ball screws and sliders, and each leg forms two stable triangle structures at any moment, which is simple but has high structure stability. The positional posture model and statics model are built and used to analyze the kinematic and mechanical properties of Rolling-Wolf. Based on these two models, important indexes for evaluating its motion performance are analyzed. According to the models and indexes, all of the structure parameters which influence the motion performance of Rolling-Wolf are optimized by the method of Archive-based Micro Genetic Algorithm（AMGA） by using Isight and Matlab software. Compared to the initial values, the maximum rotation angle of the thigh is improved by 4.17%, the maximum lifting height of the wheel is improved by 65.53%, and the maximum driving forces of the thigh and calf are decreased by 25.5% and 12.58%, respectively. The conspicuous optimization results indicate that Rolling-Wolf is much more excellent. The novel wheel-leg structure of Rolling-Wolf is efficient in promoting the load distribution, structure stability and carrying capacity of wheel-legged robot and the proposed optimization method provides a new approach for structure optimization.     

Multi-objective Genetic Optimization for LCLS-II X-ray FEL

The LCLS-II （linac coherent light source II） will build on the success of the world＇s most powerful X-ray laser： the LCLS （linac coherent light source）. It will add two new X-ray laser beams and room for additional new instruments, thus greatly increasing the number of experiments carried out each year. Multiple operation modes are proposed to accommodate a variety of user requirements. There are a large number of variables and objectives in the design. For each operation mode, MOGA （multi-objective genetic algorithm） is applied to optimize the machine parameters in order to minimize the jitters, energy spread, collective effects and emittance.     

Multi-objective optimization design and experimental investigation of centrifugal fan performance

Current studies of fan performance optimization mainly focus on two aspects： one is to improve the blade profile, and another is only to consider the influence of single impeller structural parameter on fan performance. However, there are few studies on the comprehensive effect of the key parameters such as blade number, exit stagger angle of blade and the impeller outlet width on the fan performance. The G4-73 backward centrifugal fan widely used in power plants is selected as the research object. Based on orthogonal design and BP neural network, a model for predicting the centrifugal fan performance parameters is established, and the maximum relative errors of the total pressure and efficiency are 0.974% and 0.333%, respectively. Multi-objective optimization of total pressure and efficiency of the fan is conducted with genetic algorithm, and the optimum combination of impeller structural parameters is proposed. The optimized parameters of blade number, exit stagger angle of blade and the impeller outlet width are seperately 14, 43.9~, and 21 cm. The experiments on centrifugal fan performance and noise are conducted before and after the installation of the new impeller The experimental results show that with the new impeller, the total pressure of fan increases significantly in total range of the flow rate, and the fan efficiency is improved when the relative flow is above 75%, also the high efficiency area is broadened. Additionally, in 65% -100% relative flow, the fan noise is reduced. Under the design operating condition, total pressure and efficiency of the fan are improved by 6.91% and 0.5%, respectively. This research sheds light on the considering of comprehensive effect of impeller structrual parameters on fan performance, and a new impeller can be designed to satisfy the engineering demand such as energy-saving, noise reduction or solving air pressure insufficiency for power plants.     

Proof of Concept MFD Optimization of the Aftbody Geometry of Axisymmetric Slender Body Based on Wave Drag Considerations

A comprehensive, universally valid, elegant and yet simple method to design slender axisymmetric body of minimum wave drag in transonic and supersonic flows is developed. Computational aerodynamics is also used as a tool for numerical experiments in gaining physical understanding of the drag mechanism due to the geometry of the aftbody, such as the correlation between wave drag and wave distribution of the aftbody geometry. The method utilizes MFD （modified feasible direction） based optimization program, along with the linear slender body aerodynamics, for its elegance and generic optimization convenience. The efforts are focused on inviscid flow. A practical method of reducing the wave drag of a given body is developed for both bodies with pointed end and with base area, using shock wave generator at a particular location on the aftbody. The results show that the MFD optimization program can be effectively utilized in an aerodynamic optimization problem.     

Metamodel-based global optimization using fuzzy clustering for design space reduction

High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strat     

一种基于增量元模型方法的全局优化算法

针对复杂仿真模型的全局优化问题,提出一种基于增量元模型方法的全局优化算法。首先,分析了现有增量拉丁超立方采样方法新增点数量难以控制以及其数值必须为原采样点数量的整数倍的缺陷,在此基础上利用减法规则思想改进了增量拉丁超立方采样;其次,将改进后的增量拉丁超立方采样与径向基函数的增量更新方法相结合,提出了一种全新的高效全局优化算法;最后,将该算法应用于压力容器的优化设计,计算结果证明了该方法的实用性与工程有效性。     

Secondary Lens Optimization for LED Lamps

The purpose of this paper is to present a methodology for optimizing the geometry of the LED （light emitting diode） secondary lens. The research objective is to uniform the illumination distribution on a target plane for nonimaging application. In order to achieve this, a software that simulates ray tracing is used, in conjunction with a heuristic process for enhancing the optimized parameters that form the geometry of the LED secondary lens. Spherical lenses was opted for optimization due to its lower manufacture complexity.     

Position control optimization of aerodynamic brake device for high-speed trains

The aerodynamic braking is a clean and non-adhesion braking, and can be used to provide extra braking force during high-speed emergency braking. The research of aerodynamic braking has attracted more and more attentions in recent years. However, most researchers in this field focus on aerodynamic effects and seldom on issues of position control of the aerodynamic braking board. The purpose of this paper is to explore position control optimization of the braking board in an aerodynamic braking prototype. The mathematical models of the hydraulic drive unit in the aerodynamic braking system are analyzed in detail, and the simulation models are established. Three control functions--constant, linear, and quadratic--are explored. Two kinds of criteria, including the position steady-state error and the acceleration of the piston rod, are used to evaluate system performance. Simulation results show that the position steady state-error is reduced from around 12-2 mm by applying a linear instead of a constant function, while the acceleration is reduced from 25,71-3.70 m/s2 with a quadratic control function. Use of the quadratic control function is shown to improve system performance. Experimental results obtained by measuring the position response of the piston rod on a test-bench also suggest a reduced position error and smooth movement of the piston rod. This implies that the acceleration is smaller when using the quadratic function, thus verifying the effectiveness of control schemes to improve to system performance. This paper proposes an effective and easily implemented control scheme that improves the position response of hydraulic cylinders during position control.     

Robust Design Method for Adjustable Mechanisms

Most conventional robust design methods assume design solutions are fixed values. Using these methods, designers set each control factor to a fixed value to maximize the robustness of objective characteristics. However, fluctuations in the objective characteristic often exceed the allowable range in a design problem. Consequently, it is difficult to obtain sufficient robustness using conventional methods. This research defines adjustable control factors whose values can be adjusted within a given range to increase robustness and proposes a method to calculate robustness, including factors to adjust the objective characteristic and derive optimum ranges of the factors. The robustness index, which indicates the feasibility that the objective characteristic values are within the tolerance by the adjustment, is calculated by the Monte Carlo method, while the range of adjustable control factors is optimized using the Vector evaluated particle swarm optimization. Finally, an engineering example is presented to demonstrate the applicability of the proposed method.     

基于自适应代理模型的翼型气动隐身多目标优化*

针对翼型气动隐身多目标优化设计存在的计算量大与权重难以选取的问题,提出基于自适应径向基函数代理模型与物理规划的高效多目标优化策略(Multi-objective optimization strategy using adaptive radial basis function and physical programming, ARBF-PP)。利用物理规划法通过非线性加权的方式将多目标优化问题转化为直接反映设计偏好的单目标优化问题,然后分别对综合偏好函数和约束条件构造径向基函数代理模型,采用增广Lagrange乘子法处理约束,并用遗传算法(Genetic algorithm, GA)进行求解。优化迭代过程中,在当前可能最优解附近增加样本点,更新代理模型,提高代理模型在最优解附近的近似精度,引导搜索过程快速收敛。使用数值多目标优化算例与翼型气动隐身多目标优化实例验证了本文所提出优化策略的有效性。翼型气动隐身多目标优化结果表明：相比于初始翼型,优化翼型的升阻比提高了34.28%,重点方位角的雷达散射截面(Radar cross section, RCS)均值减小了24.19%。此外,在相同样本规模的情况下,本文方法所得最优翼型的气动隐身性能比静态径向基函数代理模型方法的优化结果分别提高了11%与25.6%;与遗传算法相比,本文方法所需的分析模型调用次数(Number of evaluation function, Nfe)降低了93.5%。     

Capabilities and Performance of S-band Semi-active Multi-static Small SAR Constellation for the Equatorial Region

The attractiveness of flying several SAR （synthetic aperture radar） satellites in a semi-active configuration has been proposed by several studies. The closest implementation of such a mission scenario is exemplified by the current Terra SAR-X and Tandem-X mission, where both spacecraft are identical monostatic platforms capable of operating in various modes. The bistatic operation mode of the Tandem-X mission is a basic form of the semi-active multi-static operation mode where one satellite serves as a transmitter while the other records the scattered signals simultaneously. The use of a typical monostatic SAR spacecraft operating in-tandem with several receiver only spacecraft is a semi-active mode of operation. This paper examines the capabilities of implementing a constellation of S-band spaceborne SAR platform for alongtrack interferometry over the equatorial region for velocity measurement with particular focus on ship detection. The orbit for the mission is an inclined circular low Earth orbit, which ensures high revisit time, quick coverage and high data throughput. The pendulum configuration is adopted to maintain the relative distance between successive SAR platforms. The conditions and constraints necessary to achieve the orbit geometry required to conduct alongtrack interferometry are defined. The alongtrack separation between platforms necessary to measure specified ship velocity is also discussed. Finally an error budget estimate of the measure radial velocity is provided.     

Global optimization method using SLE and adaptive RBF based on fuzzy clustering

High fidelity analysis models,which are beneficial to improving the design quality,have been more and more widely utilized in the modern engineering design optimization problems.However,the high fidelity analysis models are so computationally expensive that the time required in design optimization is usually unacceptable.In order to improve the efficiency of optimization involving high fidelity analysis models,the optimization efficiency can be upgraded through applying surrogates to approximate the computationally expensive models,which can greately reduce the computation time.An efficient heuristic global optimization method using adaptive radial basis function(RBF) based on fuzzy clustering(ARFC) is proposed.In this method,a novel algorithm of maximin Latin hypercube design using successive local enumeration(SLE) is employed to obtain sample points with good performance in both space-filling and projective uniformity properties,which does a great deal of good to metamodels accuracy.RBF method is adopted for constructing the metamodels,and with the increasing the number of sample points the approximation accuracy of RBF is gradually enhanced.The fuzzy c-means clustering method is applied to identify the reduced attractive regions in the original design space.The numerical benchmark examples are used for validating the performance of ARFC.The results demonstrates that for most application examples the global optima are effectively obtained and comparison with adaptive response surface method(ARSM) proves that the proposed method can intuitively capture promising design regions and can efficiently identify the global or near-global design optimum.This method improves the efficiency and global convergence of the optimization problems,and gives a new optimization strategy for engineering design optimization problems involving computationally expensive models.     

Wear Analysis of Disc Cutters of Full Face Rock Tunnel Boring Machine

Wear is a major factor of disc cutters’ failure. No current theory offers a standard for the prediction of disc cutter wear yet. In the field the wear prediction method commonly used is based on the excavation length of tunnel boring machine（TBM） to predict the disc cutter wear and its wear law, considering the location number of each disc cutter on the cutterhead（radius for installation）; in theory, there is a prediction method of using arc wear coefficient. However, the preceding two methods have their own errors, with their accuracy being 40% or so and largely relying on the technicians’ experience. Therefore, radial wear coefficient, axial wear coefficient and trajectory wear coefficient are defined on the basis of the operating characteristics of TBM. With reference to the installation and characteristics of disc cutters, those coefficients are modified according to penetration, which gives rise to the presentation of comprehensive axial wear coefficient, comprehensive radial wear coefficient and comprehensive trajectory wear coefficient. Calculation and determination of wear coefficients are made with consideration of data from a segment of TBM project（excavation length 173 m）. The resulting wear coefficient values, after modification, are adopted to predict the disc cutter wear in the follow-up segment of the TBM project（excavation length of 5621 m）. The prediction results show that the disc cutter wear predicted with comprehensive radial wear coefficient and comprehensive trajectory wear coefficient are not only accurate（accuracy 16.12%） but also highly congruous, whereas there is a larger deviation in the prediction with comprehensive axial wear coefficient（accuracy 41%, which is in agreement with the prediction of disc cutters’ life in the field）. This paper puts forth a new method concerning prediction of life span and wear of TBM disc cutters as well as timing for replacing disc cutters.     

基于多组混合元模型方法的汽车轻量化设计

针对工程中复杂耗时的黑匣子问题,提出一种基于多组混合元模型的全局最优化方法。该方法同时应用三组元模型进行搜索,每组都包含克里金、二阶多项式及径向基函数的元模型。应用该优化方法对某车型的后车架进行轻量化设计后,后车架子系统的质量减少7.2kg,并提高了该子系统的刚度。研究结果表明,与HAM法相比,新方法在搜索效率和精度上都有显著提高。     

Dynamic Control of a Flexible Shaft Mounted in Adaptive or Active Bearing

The dynamic behavior of rotors is highly influenced by bearing characteristics. In previous works, the authors have shown that it may be beneficial to adapt the bearing behavior to the shaft behavior. Several adaptive and active components will be developed in this paper in order to control the shaft dynamical amplitude. Different models of hydrodynamic bearings behavior are described. The Reynolds equation resolution may be done by numerical or analytical solutions. A physical analysis of the equation of thin films will identify the most sensitive parameters. The shaft flexibility is taking into account by a modal approach. The fluid-structure coupling process is a simulation, step by step, of the rotor behavior. At each step, the nonlinear fluid force is numerically calculated to obtain the unbalanced shaft response. The results, presented in this paper, concern the dynamic response of unbalanced shaft mounted in adaptive or active bearings： bearings with variable clearance, variable viscosity or variable housing speed. It is shown that the fluid bearing parameters must be adapted to the rotor speed （in particular near or far a critical speed）. Then, the paper presents a new kind of active bearing. It works with a mechanical control of the housing position. Several parameters are tested and compared. The robustness of the dynamic control parameters is presented. In conclusion, the bearing adaptation could be very useful to control the shaft dynamic. This limits the effect of the critical speed, in particular by diminishing the shaft amplitude and the dynamic forces transmitted to the housing.     

Hybrid Improved Self-adaptive Differential Evolution and Nelder-Mead Simplex Method for Solving Constrained Real-Parameters

In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE （differential evolution） algorithm and exploitation capability of Nelder-Mead simplex method is presented （HISADE-NMS）. The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles （NP）, scaling factor （F） and crossover control （CR）, which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints.     

Localization of Small Mobile Robot by Low-Cost GPS Receiver

This article deals with a problem of the robot localization in the outdoor environment by using the GPS （global positioning system） data. In order to navigate the robot, it is necessary to transform the global position into the local map in the form of two-dimensional Cartesian coordinate system. The transformation is based on the model of the Earth-WGS 84 reference ellipsoid. The aim of this article is to experimentally evaluate a set of low-cost GPS receivers applicable as position sensors for small outdoor mobile robots. The evaluation is based on series of measurements executed in different times and places. The measured data is processed by given procedure and acquired positions are transformed into the local coordinate system. Accordingly the accuracy of the measured positions is statistically evaluated. The evaluation of used GPS receivers is done by comparison with data acquired by high-end geodetic GPS system Leica 1200, which is used as a reference GPS system.     

Evaluation of surrogate models for optimization of herringbone groove micromixer

Surrogate models have been applied to shape optimizations of a micromixer with the aim of assessing the performance of the models. The surrogate models considered include polynomial response surface approximation, Kriging, and radial basis neural network. In addition, a weighted average model based on global error measures is constructed. A mixing index at the exit of the micromixer is used as the objective function. The mixing index is calculated based on Navier-Stokes equations. Two cases of optimization, one with two design variables and the other with three design variables, have been tested. The design variables are selected among the ratio of the groove depth to channel height, the angle of groove, and the ratio of groove width to groove pitch. D-Optimal design generated sampling points are used for sampling. It is found that although the weighted average model does not predict the best optimal point, it does show consistent and reliable performance.     

基于形状特征的自由曲面建模技术

针对自由曲面重构建模中存在的问题,对曲面数字化及离散点参数优化技术进行了研究。基于自由曲面的形状特征,提出了一种曲面自适应数字化技术。建立了基于显式的最小二乘重构误差的参数优化模型,运用子空间共轭梯度内部反射牛顿优化技术实现了大规模数据点的参数优化。研究结果表明,自适应数字化技术大大提高了曲面的采样效率;参数优化模型合理且优化算法收敛迅速。