Proximal schemes for parabolic optimal control problems with sparsity promoting cost functionals

Fast first-order proximal methods that solve linear and bilinear parabolic optimal control problems with a sparsity cost functional are discussed. Weak convergence of these methods is proved and, for benchmarking purposes, the proposed inexact proximal schemes are compared to an inexact semi-smooth Newton method. Results of numerical experiments are presented to demonstrate the computational effectiveness of proximal schemes and to validate the theoretical estimates.     

Robust eigenstructure clustering by non-smooth optimisation

We extend classical eigenstructure assignment to more realistic problems, where additional performance and robustness specifications arise. Our aim is to combine time-domain constraints, as reflected by pole location and eigenvector structure, with frequency-domain objectives such as the H₂, H_∞ or Hankel norms. Using pole clustering, we allow poles to move in polydisks of prescribed size around their nominal values, driven by optimisation. Eigenelements, that is poles and eigenvectors, are allowed to move simultaneously and serve as decision variables in a specialised non-smooth optimisation technique. Two aerospace applications illustrate the power of the new method.     

Species-based Quantum Particle Swarm Optimization for economic load dispatch

Economic load dispatch (ELD) is one of the important optimization problems in the operation of power systems which can be helpful to create effective generating management plans. In this paper, the ELD problem is discussed considering transmission network losses and practical constraints of plants such as generation ramp rate, prohibited operation zones, and valve-point effects. A new method called Species-based Quantum Particle Swarm Optimization (SQPSO), which is based on the Quantum Particle Swarm Optimization (QPSO), is proposed and applied in order to solve this problem possessing non-smooth and smooth cost functions. In the proposed intelligent technique, the particles are classified according to the output results and they explore the answers in each iteration in-group form. The new method has just one control parameter. The simulation results and the numerical investigations of various examples are compared with other conventional techniques to assess the efficiency of the proposed method. The results of the numerical investigations well depict that in spite of its simplicity, the proposed method is superior over the other techniques from standpoint of optimum answer exploitation as well as possessing appropriate and acceptable speed and stability.     

仿生非光滑凹坑表面模型建立及仿真研究

仿生学研究发现非光滑表面对耐磨性有影响,并且不同的非光滑表面对耐磨性的影响不同。为了研究非光滑形态的磨损过程,基于ANSYS建立仿生非光滑凹坑表面和光滑表面的三维模型,分别对仿生非光滑凹坑表面和光滑表面滑动磨损过程进行模拟分析。结果表明非光滑表面应力集中的区域远比光滑表面的小,说明非光滑表面具有较好耐磨性。并与试验结果对比,证明建立的模型正确。     

仿生学在机械密封技术中的应用和展望

综述了仿生学和生物非光滑表面理论在工程上的应用和研究进展,明确提出可将仿生非光滑表面理论和方法应用于机械密封的设计、研究和应用中,并进行了可行性分析.     

尾部扩散器对某跑车气动性能的影响

以某跑车模型为研究对象,探讨尾部小型扩散器对于车身气动性能的影响。在初始模型的基础上,进行CFD(Computational Fluid Dynamics)数值模拟计算,并对比风洞试验数据,验证仿真的可靠性。对初始模型的扩散器进行改进设计,加大扩散器的工作区域,研究其对于气动力的影响,并将改进后的扩散器与带有仿生凹坑型非光滑扰流器结合起来,通过数值模拟方法,得出压力和速度等流场参数,比较不同形式的扩散器对于气动性能的改进效果,分析气动力改善的原因。结果表明:通过对扩散器与非光滑扰流器的优化组合,能有效地提高气动负升力,减小气动阻力,达到了调谐车辆气动升力与气动阻力之间的耦合关系的目的。     

凸包型仿生耦合金刚石钻头模拟分析

研究发现仿生耦合钻头较普通钻头钻进时效提高很多。仿生耦合钻头一方面能使钻头唇面有较高的比压;另一方面能使钻头具有很好的冷却效果,因此在钻探工程中有很好的应用前景。应用数值模拟软件ansys,模拟分析了凸包型非光滑表面对金刚石钻头性能的影响。对比分析了4种不同非光滑度状况下,钻头在一定的钻压作用下在岩石表面产生滑动摩擦的过程。主要分析了该过程中岩层的等效应力、钻头底唇面的接触摩擦应力和接触压力的变化规律。研究发现,凸包型非光滑表面在一定程度上可以提高钻头的使用寿命和钻进效率。     

低速大扭矩水压马达配流副仿生凹坑形非光滑表面流场分析

通过在低速大扭矩水压马达配流盘上设计了不同凹坑形仿生非光滑表面,并建立配流副的全水动压润滑模型,采用CFD方法研究了凹坑的不同开口形状和截面形状对内部液体流动的影响及其对流体动压润滑性能的影响规律。结果表明:在凹坑截面形状、开口尺寸及凹坑深度相同的情况下,开口形状为圆形的凹坑形仿生非光滑表面的液膜表面压力分布情况要略好于开口形状为正方形和三角形的凹坑形仿生非光滑表面的液膜表面压力分布情况;凹坑开口形状都为圆形时,截面形状为半圆形的半球坑与截面形状为矩形的圆形柱坑、截面形状为三角形的圆形锥坑相比,其液膜表面压力分布情况较好,液膜表面承载力略大,流体动压润滑性能较好。     

非单调信赖域方法求解无约束非光滑优化问题

提出了非单调信赖域算法求解无约束非光滑优化问题,并和经典的信赖域方法作比较分析。同时,设定了一些条件,在这些假设条件下证明了该算法是整体收敛的。数值实验结果表明,非单调策略对无约束非光滑优化问题的求解是行之有效的,拓展了非单调信赖域算法的应用领域。