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。     

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150 fs,满足束流稳定性的要求。     

Optimization of global kinetics parameters for heterogeneous propellant combustion using a genetic algorithm

We examine the combustion of heterogeneous propellants for which, necessarily, the chemical kinetics is modelled using simple global schemes. Choosing the parameters for such schemes is a significant challenge, one that, in the past, has usually been met using hand-fitting of experimental data (target data) for global burning properties such as steady burning rates, burn-rate temperature sensitivity, and the like. This is an unsatisfactory strategy in many ways. It is not optimal; and if the target set is large and includes such things as stability criteria, or bounds, difficult to implement. Here we discuss the use of a general optimization strategy which can handle large data sets of a general nature. The key numerical tool is a genetic algorithm that uses MPI on a parallel platform. We use this strategy to determine parameters for HMX/HTPB propellants and AP/HTPB propellants. Only one-dimensional target data are used, corresponding to the burning of pure HMX (AP) or a homogenized blend of fine HMX (AP) and HTPB. The goal is to generate kinetics models that can be used in the numerical simulation of three-dimensional heterogeneous propellant combustion. The results of such simulations will be reported in a sequel.     

Optimization and implementation of piezoelectric radiators using the genetic algorithm

Very thin and small (45 mm x 35 mm x 0.35 mm) piezoelectric radiators have been developed in this research. The system is modeled by using the energy method in conjunction with the assumed-modes method. Electrical system, mechanical system, and acoustic loading have all been accounted for during the modeling stage. On the basis of the simulation model, the genetic algorithm (GA) is employed to optimize the overall configurations for a low resonance frequency and a large gain. The resulting designs are then implemented and evaluated experimentally. Performance indices for the experimental evaluation include the frequency response, the directional response, the sensitivity, and the efficiency. It is found in the experimental results that the piezoelectric radiators are able to produce comparable acoustical output with significantly less electrical input than the voice-coil panel speakers.     

Optimization of a quantum-dot semiconductor optical amplifier (QD-SOA) design using the genetic algorithm

Optical and Quantum Electronics - We review a novel approach to the light scattering by small layered particles in the electrostatic limit when the particle is considered to be in the uniform...     

Tomographic-image reconstruction using a hybrid genetic algorithm

An improved tomographic-image reconstruction method is proposed that uses a hybrid genetic algorithm (GA) that hybridizes a conventional GA and a concurrent simplex method. For the purposes of discussion, an axisymmetric phantom density field is used with an interferometric optical projection. Tomographic-image reconstruction using the hybrid GA not only improves the convergence over the pure GA but also significantly reduces the computation time.     

Designing dispersion-compensating photonic-crystal fibers using a genetic algorithm

A genetic algorithm is combined with a fully vectorial finite-element solver to design photonic-crystal fibers (PCFs) for a broadband dispersion compensation in a generic stretcher-compressor system of an ytterbium fiber laser. Two types of PCFs are compared in terms of their dispersion-compensation capability, optical nonlinearity, and confinement loss. Fibers of the first type are standard PCFs where a solid core is surrounded by a triangular uniform lattice of identical air-holes. In PCFs of the second type, the solid core is surrounded by a dual-scale cladding, where the inner part comprises air-holes of different diameters, while the outer cladding consists of large-diameter air-holes. Second-type PCFs are shown to provide a much more accurate dispersion compensation. The influence of fiber-fabrication tolerances on the precision of dispersion compensation in short-pulse fiber laser systems is examined.     

基于多目标遗传算法的回旋行波放大器分布式损耗参数优化

通过使用多目标遗传算法对回旋行波放大器加载分布式损耗的电阻率和厚度参数进行优化,得出了两个参数的最佳组合值：损耗层厚度0.116 mm,电阻率为铜的77 882倍,此时放大器达到最大增益15.9 dB。并且通过单目标遗传算法对该值的准确性进行了验证,使得放大器在有效抑制回旋返波振荡的同时实现了增益的最大化。     

基于多目标遗传算法的回旋行波放大器分布式损耗参数优化

通过使用多目标遗传算法对回旋行波放大器加载分布式损耗的电阻率和厚度参数进行优化,得出了两个参数的最佳组合值:损耗层厚度0.116mm,电阻率为铜的77 882倍,此时放大器达到最大增益15.9dB。并且通过单目标遗传算法对该值的准确性进行了验证,使得放大器在有效抑制回旋返波振荡的同时实现了增益的最大化。     

Design of a biplanar gradient coil using a genetic algorithm

A biplanar z-gradient coil has been designed using a genetic algorithm, and its efficiency for producing a gradient along the axis of a solenoid magnet compared to that of a conventional Maxwell coil set. Coils of 21.8 cm by 20.9 cm area and 10 cm separation give 0.37 m Tm⁻¹ A⁻¹ with standard and maximum deviations of 2.6 and 13.1% of this value over an optimised cuboid region of 12 by 15 by 1.8 cm. The experimentally useable linear volume extends beyond this to 50% of the separation between the planes. Design data are also given for a transverse gradient set.     

基于加权实数编码遗传算法的超材料优化设计

针对超材料优化设计参数多、权重各异的特点,提出一种基于加权实数编码的遗传算法,该算法采用等位基因或双倍基因实现对遗传基因的加权编码,是二进制编码中加权思想的推广,与普通遗传算法相比,加权实数编码遗传算法加入了人工选择因素,既可以加快种群收敛速度,又可以提高算法的求解质量,尤其适用于种群规模较大的遗传优化计算,文中以一个超材料吸波体的优化设计为例,对算法进行了验证。     

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.     

Design of wavelength-selective waveplates using genetic algorithm

Wavelength-selective waveplates, which act either identically or differently for plural wavelengths, are useful for optical systems that handle plural wavelengths. However, they cannot be analytically designed because of the complexity of their structure. Genetic algorithm is one of the methods for solving optimization problems and is used for several kinds of optical design (e.g., design of thin films, diffractive optical elements, and lenses). I considered that it is effective for designing wavelength-selective waveplates also and tried to design them using the genetic algorithm for the first time to the best of my knowledge. As a result, four types of wavelength-selective waveplate for three wavelengths (405, 650, and 780 nm) were successfully designed. These waveplates are useful for Blu-ray Disc/Digital Versatile Disc/Compact Disc compatible optical pickups.     

Analysis of optical rib self-imaging multimode interference (MMI) waveguide devices using the discrete spectral index method

We have developed a semianalytical approach to study the propagation characteristics of multimode interference (MMI) waveguide structures. The effect of transverse crosssection geometry on self-imaging length and optical power throughput are investigated. We present results confirming that the nonquadratic modal dispersion encountered in stripe-loaded waveguides impairs self-imaging performance. Results indicate that the image degradation is more predominant for asymmetrically fed MMI waveguides.     

Improve accuracy of laser beam width measurement using a genetic algorithm

Beam width measurements of laser beams based on CCD by the second moment method as proposed by International Standardization Organization, are excessively sensitive to the noise far from light beam center. A novel method of noise elimination based on the analysis of the influence from CCD noise on laser beam width measurement result is proposed. The appropriate integral region could be obtained by genetic algorithm to improve accuracy of laser beam width measurement. The experimental results show that method could tolerate heavy CCD noise, and define the corresponding integral region according to requested precision.     

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.     

Chaos-based image encryption using a hybrid genetic algorithm and a DNA sequence

The paper studies a recently developed evolutionary-based image encryption algorithm. A novel image encryption algorithm based on a hybrid model of deoxyribonucleic acid (DNA) masking, a genetic algorithm (GA) and a logistic map is proposed. This study uses DNA and logistic map functions to create the number of initial DNA masks and applies GA to determine the best mask for encryption. The significant advantage of this approach is improving the quality of DNA masks to obtain the best mask that is compatible with plain images. The experimental results and computer simulations both confirm that the proposed scheme not only demonstrates excellent encryption but also resists various typical attacks.     

Particle Tracking Velocimetry using the genetic algorithm

A new concept genetic algorithm (GA) has been implemented and tested for the use in the 2-D and 3-D Particle Tracking Velocimetry (PTV). The algorithm is applicable to particle images with larger (greater than 2000) number of particles without losing the excellent accuracy in the particle matching results. This is mainly due to a new fitness function as well as unique genetic operations devised especially for the purpose of particle matching problem. The new fitness function is based on the relaxation of movement of a group of particles and is particularly suited for an increased density of particle images. The unique genetic operations give rise to the concentration of more fit genes in the forward part of the gene strings where the crossover and mutation processes are suppressed. The new algorithm also profits from the new genetic encoding scheme which can deal with the loss-of-pair particles (i.e., those particles which exist in one frame but do not have their matching pair in the other frame), a typical problem in the real image particle tracking velocimetry. In the present study, the new method is tested with 2-D and 3-D synthetic as well as real particle images with a large number of particles.     

Broad omnidirectional reflectors design using genetic algorithm

A application of genetic algorithm in designing omnidirectional reflectors is reported in this paper. Based on different quasi-periodic dielectric multilayer stacks, we give some optimization examples concerning both quart-wave and non quart-wave systems, and finally we achieve a photonic heterostructure with very broad omnidirectional reflection bandwidth.