Passive vibration control of a satellite boom structure by geometric optimization using genetic algorithm

In this paper, the superior mid-frequency vibration isolation of a geometrically optimized lightweight structure is demonstrated. The initial structure under test here was a 4.5 m long satellite boom consisting of 10 identical bays with equilateral triangular cross-sections. An unusual geometric variant of this, with inherent isolation characteristics, has been designed by the use of genetic algorithm (GA) methods. In order to obtain the best design, the joints in the boom were allowed to move around by 20% of the length of each bay (i.e., ±9 cm in all three translational directions). This work is based on results from a Fortran code (which was derived from receptance analysis) that are fully validated against detailed finite element (FE) models of the structure. The experimental forced response of the regular boom structure has been measured and compared with predicted curves. Finally, having obtained the geometrically optimized boom structure, its experimental response is compared with the theoretical results predicted by the receptance method. It is shown that the average of 30 dB isolation in the vibration energy transfer between the ends of the network of beams, over a 100 Hz bandwidth predicted in the design process, is achieved experimentally in an essentially undamped structure.     

基于遗传算法的光学膜系初始结构优化设计

膜系初始结构优化设计是膜系优化设计的关键。针对多膜料设计 ,提出了一种新的膜系初始结构优化设计算法 ,将膜系的初始设计视为组合优化问题 ,采用遗传算法 ,求得组合的最优解。给出了算法的原理 ,并给出了相应的设计实例。结果表明 ,本算法是一种简单、有效、通用性强的膜系初始化设计方法     

Multi-objective optimization of ring stiffened cylindrical shells using a genetic algorithm

In this paper, the genetic algorithm (GA) method is used for the multi-objective optimization of ring stiffened cylindrical shells. The objective functions seek the maximum fundamental frequency and minimum structural weight of the shell subjected to four constraints including the fundamental frequency, the structural weight, the axial buckling load, and the radial buckling load. The optimization process contains six design variables including the shell thickness, the number of stiffeners, the width and height of stiffeners, the stiffeners eccentricity distribution order, and the stiffeners spacing distribution order. The real coding scheme is used for representing the solution string, while the generation number-based adaptive penalty function is applied for penalizing infeasible solutions. In analytical solution, the Ritz method is applied and the stiffeners are treated as discrete elements. Some examples of simply supported cylindrical shells with nonuniform eccentricity distribution and nonuniform rings spacing distribution are provided to demonstrate the optimality of the solution obtained by the GA technique. The effects of objective weighting coefficients and bounding values of the design variables on the optimum solution are studied for various cases. The results show that the optimal solution can vary with the weighting coefficients significantly. It is also found that extreme reduction and augmentation in turn in the structural weight and fundamental frequency can be simultaneously achieved by selecting suitable stiffeners’ geometrical parameters and distributions. Furthermore, the bounding values of the design variables have great effects on the optimum results.     

丙酮分子的共振增强多光子电离解离过程的实验研究

报道了在280—286.5nm区域内，通过共振增强多光子电离-飞行时间质谱和质量选择光电离激发谱对丙酮分子的光电离和光解离通道进行了研究，并对部分碎片离子的分质量激发谱进行了归属和标识.实验结果表明，在280—286.5nm紫外光波段内，丙酮分子以母体分子的电离通道为主，即首先电离生成母体离子然后母体离子再吸收光子解离生成碎片离子. 关键词： 丙酮 共振增强多光子电离 飞行时间质谱     

遗传算法在柱状高温气冷堆换料优化问题中的应用

堆芯换料方案的优化是一个典型的组合优化问题,其搜索空间异常庞大。传统的优化算法很难在如此巨大的搜索空间中寻找出全局最优解。遗传算法以其优良的自适应能力和优化能力,为组合优化问题提供了一个非常有效的解决途径。采用遗传算法对柱状高温气冷堆堆芯装料方案进行了优化,并编写了相应程序。为了提高堆物理的计算精度,堆芯临界计算采用26群输运计算。由于多群输运计算需要大量计算时间,为此对遗传算法进行了并行优化。为了验证遗传算法对柱状高温气冷堆换料的优化能力,构造了一个8组件的小型柱状高温气冷堆换料优化基准题。结果表明,遗传算法在柱状高温气冷堆换料优化问题中具有良好的优化能力和计算稳定性。     

遗传算法在柱状高温气冷堆换料优化问题中的应用

堆芯换料方案的优化是一个典型的组合优化问题,其搜索空间异常庞大。传统的优化算法很难在如此巨大的搜索空间中寻找出全局最优解。遗传算法以其优良的自适应能力和优化能力,为组合优化问题提供了一个非常有效的解决途径。采用遗传算法对柱状高温气冷堆堆芯装料方案进行了优化,并编写了相应程序。为了提高堆物理的计算精度,堆芯临界计算采用26群输运计算。由于多群输运计算需要大量计算时间,为此对遗传算法进行了并行优化。为了验证遗传算法对柱状高温气冷堆换料的优化能力,构造了一个8组件的小型柱状高温气冷堆换料优化基准题。结果表明,遗传算法在柱状高温气冷堆换料优化问题中具有良好的优化能力和计算稳定性。     

ZnO thin film characterization by X-ray reflectivity optimization using genetic algorithm and Fourier transformation

Zinc oxide (ZnO) thin film was fabricated by sol-gel spin coating method on glass substrate. X-ray reflectivity (XRR) and its optimization have been used for characterization and extracting physical parameters of the film. Genetic algorithm (GA) has been applied for this optimization process. The model independent information was needed to establish data analyzing process for X-ray reflectivity before optimization process. Independent information was exploited from Fourier transform of Fresnel reflectivity normalized X-ray reflectivity. This Fourier transformation (Auto Correlation Function) yields thickness of each coated layer on substrate. This information is a keynote for constructing optimization process. Specular X-ray reflectivity optimization yields structural parameters such as thickness, roughness of surface and interface and electron density profile of the film. Acceptable agreement exists between results obtained from Fourier transformation and X-ray reflectivity fitting.     

800 nm激光作用下碘乙烷的多光子电离解离研究

在800nm飞秒激光作用下对碘乙烷多光子电离解离过程进行了研究,获得了碘乙烷分子的多光子电离飞行时间（MPI-TOF）质谱.光强指数分析表明母体离子主要发生3+3共振增强多光子电离（REMPI）过程.根据部分碎片离子占总离子信号的百分比对激光强度的依赖关系,讨论了碘乙烷的多光子电离解离机制,得出了C₂H₅I分子的多光子电离（MPI）属于母体离子离解阶梯模式.文中分析了母体离子在该波长下主要两条解离通道,其中C-I键的断裂为主要通道.应用高斯03在B3LYP/3-21G基组上计算了两条通道能量的变化,理论进一步验证了实验结果的合理性.     

Performance optimization for terahertz quantum cascade laser at higher temperature using genetic algorithm

The aim of this work is to establish an approach for obtaining improved design parameters for high temperature operation of terahertz quantum cascade lasers using a multi-objective evolutionary algorithm. For studying the lasing conditions of a quantum cascade laser, a self-consistent model is adopted. This model uses standard wave function approximation and effective mass approximation with relevant scattering mechanisms to solve Schrodinger’s equation for the cascaded quantum wells. Fermi’s Golden Rule is then used to calculate the corresponding lifetime of each eigen states. To describe the coherent evolution of wave functions and phase breaking, density matrix formalism is employed. Subsequently, laser rate equations are used for calculating the parameters related to electronic transport in the device. These parameters are then utilized for investigating the temperature dependence of existing terahertz quantum cascade lasers. Finally, using an optimization technique based on Genetic algorithm, design parameters for resonant-phonon quantum cascade laser are obtained within the terahertz frequency range. The results illustrate that this optimization process can offer improvement in the performance of quantum cascade lasers in terahertz region at an elevated temperature. Moreover, the results also reveal that significant increase in operating temperature of a resonant phonon terahertz QCL is unlikely and hence novel design approaches should be considered for operating THz QCLs at room temperature.     

Multiobjective optimization of the synchrotron radiation source Siberia-2 lattice using a genetic algorithm

Numerical simulation is one of the most efficient methods of investigating and optimizing nonlinear effects. However, simulating complex processes considering numerous nonlinear effects with the use of classical optimization methods is very difficult. This work deals with the application of a multiobjective genetic algorithm for the optimization of lattices of synchrotron radiation sources. This algorithm allows one to efficiently optimize both the linear and complex strongly nonlinear lattices of accelerators to obtain the required facility parameters.     

Identification of noise sources in factory’s sound field by using genetic algorithm

Noise control is important and essential in factory, where the noise level is restricted by the Occupational Safety and Health Act. Before noise abatement being performed, the identification work in searching for the location and sound power level (SWL) of noisy sound sources is absolutely prerequisite. Several researches on new techniques of single noise control have been well addressed and developed; however, the research work on sound identification for the existing multi-noise plant is hardly found sufficient. Under the circumstance of unrecognized noises, the noise control work will expectedly be extravagant and fruitless. Therefore, the numerical approach in distinguishing noises from a multi-noise plant becomes crucial and obligatory.In this paper, the novel technique of genetic algorithm (GA) in conjunction with the method of minimized variation square will be adopted and used in the following numerical optimization. In addition, various sound monitoring systems in detecting the noise condition within the plant area will also be introduced. Before noises identification, the accuracy of mathematical model has then been proved to be in good agreements comparing to the simulated data of SoundPlan, a commercialized simulation package in sound field. Moreover, three kinds of multi-noise plants have been fully discussed and acknowledged by GA optimization. The results reveal that the relevant locations and sound power levels (SWLs) of noises can be precisely recognized. This paper surely provides a rapid methodology in the noise identification work for a multi-noise plant.     

基于遗传算法的不等间距阵优化方法*

阵元数一定情况下,针对不等间距拖线阵高频信号处理存在的空间增益和无栅瓣兼容问题,提出一种基于遗传算法的不等间距拖线阵阵型优化方法。该方法以频带交互下最大旁瓣级最小作为约束因子,通过模拟生物自然进化过程搜索全局最优解,得到优化后的阵元位置。优化后阵型在保证低频信号处理空间增益不变情况下,实现对高频信号高空间增益、无栅瓣处理。计算机仿真结果表明：相比未优化阵型,在高频信号处理方面,优化后阵型在无栅瓣情况下,空间增益提升值近似理论值提升值;在低频信号处理方面,优化后阵型具有相同的空间增益。为实际不等间距拖线阵阵型优化和应用提供了一种思路。     

Optimal piezoelectric actuator and sensor location for active vibration control, using genetic algorithm

This paper deals with the optimization of piezoelectric actuators and sensors locations for active vibration control. Two modified optimization criteria are used, ensuring good observability or controllability of the structure, and considering residual modes to limit the spillover effect. Two optimization variables are considered for each piezoelectric device: the location of its center and its orientation. Genetic algorithms are used to find the optimal configurations. Several simulations are presented for a simply supported plate.     

基于克隆选择的混合遗传算法在碳纳米管结构优化中的研究

针对分子动力学模拟中碳纳米管的结构优化问题，提出了一种新的优化算法.新的优化算法在遗传算法的基础上，引入了克隆选择机理和模拟退火技术.对五个典型函数的优化测试结果表明，该算法搜索过程稳定性好，可较好地实现全局最优.将其应用于碳纳米管原子结构优化，加快了能量优化速度，提高了优化质量.模拟结果说明，混合遗传算法的优化时间随原子数增加而呈线性增长.在碳纳米管原子数较多时，结构优化时间比共轭梯度法降低一个数量级左右，大大降低了系统的模拟时间. 关键词： 分子动力学 碳纳米管 能量优化 遗传算法 克隆选择算法     

Structural damage evaluation using genetic algorithm

The detection and identification of structural damage is important in monitoring of structural systems during their lifetime. Many researchers have proposed a variety of damage evaluation methods based on structural monitoring. The stiffness matrix is used in some conventional damage detection methods; however, it leads to inevitable error due to the lack of data provided by structural monitoring. To overcome this problem, this study introduces a new damage evaluation method that identifies the structural damage in a shear building based on a genetic algorithm using the structural flexibility matrix with dynamic analyses. The proposed method enables the deduction of the extent and location of structural damage, even when there is insufficient data on the dynamic characteristics and insufficient accurate measurements of the structural stiffness and mass. The validity of the proposed damage evaluation method is demonstrated through numerical analyses using OpenSees.     

Optimal vibration control of smart fiber reinforced composite shell structures using improved genetic algorithm

In the present article, an improved genetic algorithm (GA) based optimal vibration control of smart fiber reinforced polymer (FRP) composite shell structures has been presented. Layered shell finite elements have been formulated and the formulation has been validated for coupled electromechanical analysis of curved smart FRP composite structures having piezoelectric sensors and actuators patches. An integer-coded GA-based open-loop procedure has been used for optimal placement of actuators for maximizing controllability index and a real-coded GA-based linear quadratic regulator (LQR) control scheme has been implemented for optimal control of the smart shell structures in order to maximize the closed-loop damping ratio while keeping actuators voltages within the limit of breakdown voltage. Results obtained from the present work show that this combined GA-based optimal actuators placement and GA-based LQR control scheme is far superior to conventional active vibration control using LQR schemes and simple placement of actuators reported in literatures. Results also show that the present improved GA-based combined optimal placement and LQR control scheme not only leads to increased closed-loop damping ratio but also shows a drastic reduction in input/actuation voltage compared to the already published results.     

基因算法在光阴极注入器优化设计中的应用

基于正在建设的大连自由电子激光装置,研究了基因算法在注入器优化设计中的系统应用。与传统的注入器优化方法相比较,基因算法在多变量、多目标注入器优化问题中具有优化效率高、优化结果精确的优势;通过采用权重因子的方法将多目标问题转化为单目标优化问题,大大简化了基因算法优化流程;光阴极注入器对束流稳定性要求严格,通过基因算法优化使束流的到达时间抖动控制到150fs,满足束流稳定性的要求。