Topology Optimization of Sound-Absorbing Materials for Two-Dimensional Acoustic Problems Using Isogeometric Boundary Element Method

In this work,an acoustic topology optimizationmethod for structural surface design covered by porous materials is proposed.The analysis of acoustic problems is performed using the isogeometric boundary elementmethod.Taking the element density of porousmaterials as the design variable,the volume of porousmaterials as the constraint,and the minimum sound pressure or maximum scattered sound power as the design goal,the topology optimization is carried out by solid isotropic material with penalization(SIMP)method.To get a limpid 0–1 distribution,a smoothing Heaviside-like function is proposed.To obtain the gradient value of the objective function,a sensitivity analysis method based on the adjoint variable method(AVM)is proposed.To find the optimal solution,the optimization problems are solved by the method of moving asymptotes(MMA)based on gradient information.Numerical examples verify the effectiveness of the proposed topology optimization method in the optimization process of two-dimensional acoustic problems.Furthermore,the optimal distribution of sound-absorbingmaterials is highly frequency-dependent and usually needs to be performed within a frequency band.

Study on the Optimization of Two-dimensional Electrophoresis Technology System for Rapeseed Proteome

[Objective] The research aimed to establish the two-dimensional electrophoresis（2-DE）technology which was suitable for the rapeseed proteome research.[Method] Xiangyou 17 was as the material.The sample preparation method,gel concentration and loading amount,etc.in 2-DE technology were optimized.[Result] The best extraction method of total protein of rapeseed was TCA-acetone method,and the protein spots on 2-DE map were the most.When IPG strip（pH 3-10）and 12% gel were used,and the loading amount was 250 μg,the two-dimensional electrophoresis map with the clear background,good repeatability and high protein spot resolution was obtained.[Conclusion] The research laid the foundation for carrying out the rapeseed proteomics research.

二维矩形Strip Packing问题的算法研究与改进

二维矩形Strip Packing问题的约束条件及目标函数与基本型二维矩形Packing问题类似,都是在有限的矩形容器中,有效地摆放各个矩形块,以最大化容器利用率为目标。为了解决这一NP-hard问题,该文在邓见凯、王磊提出的拟人型全局优化算法的基础上进行了深入的算法研究与改进。针对Strip Packing问题特点,提出了QHG(Quasi-Human Group)算法,其核心改进涵盖了多个方面,包括扩充初始点集合、删除和替换评价标准以及扩大邻域空间搜索范围。和单个局部极小值点的迭代相比,对局部极小值点集合进行迭代所生成布局优度更高,跳坑策略用于跳出局部极小值点,将搜索引向有希望的区域,优美度枚举有望进一步提高布局优度。通过这些措施,QHG算法更好地模拟人类决策过程,提高了全局搜索的效率。为评估QHG算法性能,对8组标准问题实例(C组、N组、NT组、CX组、NP组、ZDF组、2sp组、bwmv组)进行了大量实验。实验结果表明,QHG算法生成的布局优度优于当前国际文献中的几种较先进算法,展现了其在Strip Packing问题上的卓越性能。

A Particle Swarm Optimization Algorithm for a 2-D Irregular Strip Packing Problem

Two-Dimensional Irregular Strip Packing Problem is a classical cutting/packing problem. The problem is to assign, a set of 2-D irregular-shaped items to a rectangular sheet. The width of the sheet is fixed, while its length is extendable and has to be minimized. A sequence-based approach is developed and tested. The approach involves two phases;optimization phase and placement phase. The optimization phase searches for the packing sequence that would lead to an optimal (or best) solution when translated to an actual pattern through the placement phase. A Particle Swarm Optimization algorithm is applied in this optimization phase. Regarding the placement phase, a combined algorithm based on traditional placement methods is developed. Competitive results are obtained, where the best solutions are found to be better than, or at least equal to, the best known solutions for 10 out of 31 benchmark data sets. A Statistical Design of Experiments and a random generator of test problems are also used to characterize the performance of the entire algorithm.

Image Thresholding Using Two-Dimensional Tsallis Cross Entropy Based on Either Chaotic Particle Swarm Optimization or Decomposition

The segmentation effect of Tsallis entropy method is superior to that of Shannon entropy method, and the computation speed of two-dimensional Shannon cross entropy method can be further improved by optimization. The existing two-dimensional Tsallis cross entropy method is not the strict two-dimensional extension. Thus two new methods of image thresholding using two-dimensional Tsallis cross entropy based on either Chaotic Particle Swarm Optimization (CPSO) or decomposition are proposed. The former uses CPSO to find the optimal threshold. The recursive algorithm is adopted to avoid the repetitive computation of fitness function in iterative procedure. The computing speed is improved greatly. The latter converts the two-dimensional computation into two one-dimensional spaces, which makes the computational complexity further reduced from O(L2) to O(L). The experimental results show that, compared with the proposed recently two-dimensional Shannon or Tsallis cross entropy method, the two new methods can achieve superior segmentation results and reduce running time greatly.

An Optimization Model for the Strip-packing Problem and Its Augmented Lagrangian Method

This paper formulates a two-dimensional strip packing problem as a non- linear programming （NLP） problem and establishes the first-order optimality conditions for the NLP problem. A numerical algorithm for solving this NLP problem is given to find exact solutions to strip-packing problems involving up to 10 items. Approximate solutions can be found for big-sized problems by decomposing the set of items into small-sized blocks of which each block adopts the proposed numerical algorithm. Numerical results show that the approximate solutions to big-sized problems obtained by this method are superior to those by NFDH, FFDH and BFDH approaches.

Effects of fluid flow rate and viscosity on gravel-pack plugging and the optimization of sand-control wells production

Series of experiments were performed to simulate the invasion of formation sand into and the plugging process of gravel-pack at different viscosities and flowing rates of fluid.Two types of formation sands with the medium size of 0.10 mm and 0.16 mm and the quartz sand and ceramsite of 0.6-1.2 mm were used in the experiments.A new viscosity-velocity index(the product of fluid viscosity and velocity)was put forward to characterize the influencing mechanism and law of physical property and flow condition of formation fluid on gravel-pack plugging,and a new method to optimize the production rate of wells controlling sand production with gravel-packing was proposed.The results show that the permeability of formation sand invaded zone and final permeability of plugged gravel-pack have negative correlations with viscosity and flow velocity of fluid,the higher the flow velocity and viscosity,the lower the permeability of formation sand invaded zone and final permeability of plugged gravel-pack will be.The flow velocity and viscosity of fluid are key factors affecting plugging degree of the gravel zone.The viscosity-velocity index(v-v index)can reflect the flow characteristics of fluid very well and make it easier to analyze the plugging mechanism of gravel zone.For different combinations of fluid viscosity and flow velocity,if the v-v index is the same or close,their impact on the final gravel permeability would be the same or close.With the increase of the v-v index,the permeability of plugged gravel zone decreases first,then the reduction rate slows down till the permeability stabilizes.By optimizing production and increasing production step by step,the optimal working scheme for sand-control well can reduce the damage to gravel-pack zone permeability caused by sand-carrying fluid effectively,and increase well productivity and extend the sand control life.

基于粗精调技术的求解带平衡约束圆形Packing问题的拟物算法

带平衡约束的圆形Packing问题是以卫星舱布局为背景的具有NP难度的布局优化问题.文中建立了此问题相应的数学模型,同时提出了两个新的物理模型,并受工艺加工过程中"粗精加工"现象的启发,提出了基于粗精调技术的拟物算法QPCFA.该算法既兼顾了搜索空间的多样性以利于全局搜索,又能对有前途的局部区域进行精细搜索以找到相应的局部最优解.同时,在计算过程中引入禁忌技术和跳坑策略,以提高算法的求解质量.对国际上11个代表性的算例进行了计算,QPCFA更新了其中7个算例的最好记录,其余4个与目前的最好记录基本持平,且与目前的最好结果相比在计算精度上均有较大的提高.

基于格局变换策略的不等圆Packing问题求解算法

采用基于格局变换策略的算法ACP-Solver求解不等圆Packing问题。ACP-Solver由连续优化方法、格局变换算子和接收准则组成。连续优化方法可从任一初始格局收敛至对应的局部最优格局。格局变换算子将当前格局变换为新格局。接收准则决定是否接收变换所得格局。基于24个国际公开算例的计算实验表明,ACP-Solver能在可接受的计算时间内改进或持平绝大多数算例的当前最优记录。实验结果表明了ACP-Solver的高效性能。

一种求解二维矩形Packing问题的拟人型全局优化算法

针对二维矩形Packing问题,提出了基于占角动作的基本算法。以基本算法为基础,提出了三阶段优化的拟人型全局优化算法。在第一阶段生成初始布局。在第二阶段交替调用邻域搜索子程序和跳坑策略子程序对矩形块的优先级排序进行优化。邻域搜索采用交换式和插入式两种邻域结构,避免单一邻域结构的局限性。当搜索遇到局部最优解时,采用跳坑策略子程序跳出局部最优解,将搜索引向有希望的区域。在第三阶段调用优美度枚举子程序对占角动作的选择作进一步优化。提出了两条优度定理。对于六组benchmark测试用例的实验结果表明,算法的整体表现优于当前文献中的先进算法。针对矩形块方向固定的情形,算法对zdf6和zdf7两个问题实例得到了比已有文献记录更优的布局。

求解一刀切式二维矩形Strip Packing问题的混合搜索算法

一刀切式二维矩形Strip Packing问题是一种NP难度问题。问题的实用背景是诸如玻璃板材切割、集成电路布局等工业生产中,需要优化布局和切割方案以提高利用率。总体框架是首先针对二维矩形Packing问题提出混合搜索算法,然后采用跳跃式查找与折半查找相结合的方式,将混合搜索算法用于求解二维矩形Strip Packing问题。从拟人途径提出占角、动作空间、极高度、组合拼凑等基本定义以及基本算法。以基本算法为基础,混合搜索算法分为3个阶段:第一阶段生成初始解。第二阶段调用邻域搜索子程序对矩形块的优先级进行调整。当邻域搜索遇到局部最优解时,采用基于随机扰动的跳坑策略子程序跳出局部最优陷阱,并在新区域继续搜索。第三阶段调用优美度枚举子程序对占角动作的选择进行优化。混合搜索算法计算了2组共91个benchmark实例,并将其计算结果与SPTRS算法进行了比较。SPTRS算法计算结果的平均相对误差是4.26%,混合搜索算法计算结果的平均相对误差是3.83%。因此,混合搜索算法是一种求解一刀切式二维矩形Strip Packing问题的高效启发式算法。

Protein Conformational Change Based on a Two-dimensional Generalized Langevin Equation

A two-dimensional generalized Langevin equation is proposed to describe the protein conformational change, compatible to the electron transfer process governed by atomic packing density model. We assume a fractional Gaussian noise and a white noise through bond and through space coordinates respectively, and introduce the coupling effect coming from both fluctuations and equilibrium variances. The general expressions for autocorrelation functions of distance fluctuation and fluorescence lifetime variation are derived, based on which the exact conformational change dynamics can be evaluated with the aid of numerical Laplace inversion technique. We explicitly elaborate the short time and long time approximations. The relationship between the two-diraensional description and the one-dimensional theory is also discussed.

New two-dimensional fuzzy C-means clustering algorithm for image segmentation

To solve the problem of poor anti-noise performance of the traditional fuzzy C-means (FCM) algorithm in image segmentation, a novel two-dimensional FCM clustering algorithm for image segmentation was proposed. In this method, the image segmentation was converted into an optimization problem. The fitness function containing neighbor information was set up based on the gray information and the neighbor relations between the pixels described by the improved two-dimensional histogram. By making use of the global searching ability of the predator-prey particle swarm optimization, the optimal cluster center could be obtained by iterative optimization, and the image segmentation could be accomplished. The simulation results show that the segmentation accuracy ratio of the proposed method is above 99%. The proposed algorithm has strong anti-noise capability, high clustering accuracy and good segment effect, indicating that it is an effective algorithm for image segmentation.

Symmetry Reduction of Two-Dimensional Damped Kuramoto-Sivashinsky Equation

In this paper, the problem of determining the largest possible set of symmetries for an important nonlinear dynamical system： the two-dimensional damped Kuramoto-Sivashinsky （（21）） DKS ） equation is studied. By applying the basic Lie symmetry method for the （217）） DKS equation, the classical Lie point symmetry operators are obtained. Also, the optimal system of one-dimensional subalgebras of the equation is constructed. The Lie invariants as well as similarity reduced equations corresponding to infinitesimal symmetries are obtained. The nonclassicaJ symmetries of the （2D） DKS equation are also investigated.

Two-dimensional cross entropy multi-threshold image segmentation based on improved BBO algorithm

In order to improve the global search ability of biogeography-based optimization(BBO)algorithm in multi-threshold image segmentation,a multi-threshold image segmentation based on improved BBO algorithm is proposed.When using BBO algorithm to optimize threshold,firstly,the elitist selection operator is used to retain the optimal set of solutions.Secondly,a migration strategy based on fusion of good solution and pending solution is introduced to reduce premature convergence and invalid migration of traditional migration operations.Thirdly,to reduce the blindness of traditional mutation operations,a mutation operation through binary computation is created.Then,it is applied to the multi-threshold image segmentation of two-dimensional cross entropy.Finally,this method is used to segment the typical image and compared with two-dimensional multi-threshold segmentation based on particle swarm optimization algorithm and the two-dimensional multi-threshold image segmentation based on standard BBO algorithm.The experimental results show that the method has good convergence stability,it can effectively shorten the time of iteration,and the optimization performance is better than the standard BBO algorithm.

Adaptive stochastic resonance method for weak signal detection based on particle swarm optimization

In order to solve the parameter adjustment problems of adaptive stochastic resonance system in the areas of weak signal detection,this article presents a new method to enhance the detection efficiency and availability in the system of two-dimensional Duffing based on particle swarm optimization.First,the influence of different parameters on the detection performance is analyzed respectively.The correlation between parameter adjustment and stochastic resonance effect is also discussed and converted to the problem of multi-parameter optimization.Second,the experiments including typical system and sea clutter data are conducted to verify the effect of the proposed method.Results show that the proposed method is highly effective to detect weak signal from chaotic background,and enhance the output SNR greatly.

面向不等圆Packing问题的群智能劳动分工方法

针对具有非确定性多项式难度(NP-hard)的全局优化问题-不等圆Packing问题(UCPP),基于空间分配思路提出新的求解方法-群智能劳动分工(SILD)方法.从空间的角度来看,不等圆Packing问题就是将容器空间合理高效地分配给圆形物体.所提出方法的核心思想在于将不等圆Packing问题抽象为空间分配问题,利用群智能劳动分工的任务分配来实现不等圆Packing问题的空间分配.从分配的角度对比分析不等圆Packing问题和群智能劳动分工,将圆形物体执行的动作看作个体执行的任务,分别为动作和圆形物体设计环境刺激和响应阈值.在群智能劳动分工刺激-响应原理作用下,圆形物体选择恰当的动作完成空间分配.实际工程算例和基准函数算例的测试结果表明,所提出方法是求解不等圆Packing问题的有效算法.

Innovative design and optimization of a two-dimensional deployable nine-grid planar antenna mechanism with a flat reflection surface

With the development of the aerospace industry,space missions are becoming more complicated and diversified,and there is a demand for antenna mechanisms with a larger physical aperture.In this paper,a planar deployable mechanism is proposed,which can form a flat reflection surface with a small gap between plates.To this end,a novel large-scale two-dimensional deployable nine-grid planar antenna mechanism is designed.First,two antenna folding schemes and four supporting mechanism schemes are proposed.Through comparison analysis,the antenna configuration scheme with the best comprehensive performance is selected.A kinematic model of the deployable mechanism is established,and its kinematic characteristics are analyzed.Then,the correctness of the kinematic model is verified by comparing the analytical and simulation results of the kinematic model.Subsequently,a finite element model of the antenna is developed.Based on the response surface method,the structural parameters of the support rods of the antenna are optimized,and a set of optimized solutions with lightweight and high fundamental frequency characteristics are obtained.Finally,a prototype of the proposed nine-grid planar antenna is fabricated.The feasibility of the deployment principle and the rationality of the designed mechanism are verified by deployment experiments.

Decision Support through Intelligent Agent Based Simulation and Multiple Goal Based Evolutionary Optimization

Agent based simulation has successfully been applied to model complex organizational behavior and to improve or optimize aspects of organizational performance. Agents, with intelligence supported through the application of a genetic algorithm are proposed as a means of optimizing the performance of the system being modeled. Local decisions made by agents and other system variables are placed in the genetic encoding. This allows local agents to positively impact high level system performance. A simple, but non trivial, peg game is utilized to introduce the concept. A multiple objective bin packing problem is then solved to demonstrate the potential of the approach in meeting a number of high level goals. The methodology allows not only for a systems level optimization, but also provides data which can be analyzed to determine what constitutes effective agent behavior.

Static Optimization of a Compliant Vertical Access Riser

The compliant vertical access riser (CVAR) is a new riser concept with good compliance;it can significantly reduce operating costs by eliminating the need for additional machines to operate wells directly on the platform.In this study,we determined the optimal riser parameters in terms of the stress and riser weight by optimizing the CVAR,and we compared the optimization resuits.A two-dimensional nonlinear static CVAR model was deduced according to the principles of virtual work and variation,and the model was verified using MATLAB.Design of experiments and Kriging method were used to reduce the number of sample calculations and improve the modeling accuracy.An appropriate selection of the multi-objective optimization problem (MOP) and the non-dominated sorting genetic algorithm helped to optimize the CVAR design.The non-dominated sorting genetic algorithm Ⅱ was used to solve the Pareto frontier of the optimization model in order to provide decision makers with more choices for the optimization results.After optimizing the riser parameters,the geometry of the riser was smoother,and the stress and stress differences were greatly reduced;the maximum equivalent stresses at the top and bottom were reduced by 36.6% and 44%,respectively.In addition,the stress difference in the buoyancy block area was reduced by 20.9%,and the weight of the riser was increased significantly by 28.1%.