强爆炸冲击波作用下天线结构的离散变量优化设计

首先建立了强爆炸冲击波作用下天线结构受精度和应力约束的连续变量优化设计数学模型 ;其次 ,根据材料特点 ,将设计变量取为离散变量 ,提出了天线结构在强爆炸冲击波作用下受精度和应力约束的离散变量优化设计数学模型。采用离散变量优化算法离散复合形法 ,对强爆炸冲击波作用下的 8m天线进行了优化计算。结果表明 ,经优化设计后 ,天线重量仅为初始重量的 4 0 %。     

Neural network optimization of material composition of a functionally graded material plate at arbitrary temperature range and temperature rise

Summary A neural network model is applied to optimization problems of material compositions for a functionally graded material plate with arbitrarily distributed and continuously varied material properties in the thickness direction. Unsteady temperature distribution is evaluated by taking into account the bounds of the number of the layers. Thermal stress components for an infinite functionally graded material plate are formulated under traction-free mechanical conditions. As a numerical example, a plate composed of zirconium oxide and titanium alloy is considered. In the optimization problem of minimizing the thermal stress distribution, the numerical calculations are carried out making use of the neural network. The optimum material composition is determined by taking into account the effect of temperature-dependence of material properties. The results obtained by neural network and ordinary nonlinear programming method are compared. Received 3 March 1998; accepted for publication 22 May 1998     

Une technique de lissage de données basée sur la théorie de la régularisationA filter technique based on regularization theory

A simple filter technique based on the regularization theory is presented. We consider the problem as an optimization one. The regularization theory gives us a suitable theoretical framework to define a functional to minimize. We make a numerical comparation between this method and a classical Fourier technique. To cite this article: J.-M. Fullana, C. R. Mecanique 330 (2002) 647–652.     

HOMOGENIZATION—BASED TOPOLOGY DESIGN FOR PURE TORSION OF COMPOSITE SHAFTS

In conjunction with the homogenization theory and the finite element method, the mathematical models for designing the corss-section of composite shafts by maximizing the torsion rigidity are developed in this paper. To obtain the extremal torsion rigidity, both the cross-section of the macro scale shaft and the representative microstructure of the composite material are optimized using the new models. The micro scale computational model addresses the problem of finding the periodic microstructures with extreme shear moduli. The optimal microstructure obtained with the new model and the homogenization method can be used to improve and optimize natural or artificial materials. In order to be more practical for engineering applications, cellular materials rather than ranked materials are used in the optimal process in the existence of optimal bounds for the elastic properties. Moreover, the macro scale model is proposed to optimize the cross-section of the torsional shaft based on the tailared composites. The validating optimal results show that the models are very effective in obtaining composites with extreme elastic properties, and the cross-section of the composite shaft with the extremal torsion rigidity. The project supported by the National Natural Science Foundation of China (10172078 and 10102018)     

基于动态布谷鸟搜索算法的PID控制器参数优化

针对传统PID控制器参数优化费时且不能保证获得最佳性能,提出一种基于动态布谷鸟搜索算法的PID控制器参数优化方法。布谷鸟搜索算法(CS)具有参数少、搜索能力强等特点,但是标准布谷鸟搜索算法参数采用固定值,极大地影响了算法的性能,因此提出了动态布谷鸟搜索算法(DCS),DCS算法采用动态参数,算法性能明显改善。仿真试验结果表明基于动态布谷鸟搜索算法的PID控制器具有较好的控制性能指标。     

A dynamic gradient approach to Pareto optimization with nonsmooth convex objective functions

In a general Hilbert framework, we consider continuous gradient-like dynamical systems for constrained multiobjective optimization involving nonsmooth convex objective functions. Based on the Yosida regularization of the subdifferential operators involved in the system, we obtain the existence of strong global trajectories. We prove a descent property for each objective function, and the convergence of trajectories to weak Pareto minima. This approach provides a dynamical endogenous weighting of the objective functions, a key property for applications in cooperative games, inverse problems, and numerical multiobjective optimization.     

Method development for compositional analysis of low molecular weight poly(vinyl acetate) by matrix-assisted/laser desorption-mass spectrometry and its application to analysis of chewing gum

The influence of the sample preparation parameters (the choice of the solvent and of the matrix:analyte ratio) was investigated and optimal conditions were established for MALDI mass spectrometry analysis of the pristine low molecular weight polyvinyl acetate (PVAc). It was demonstrated that comparison of polymer’s and solvent’s Hansen solubility parameters could be used as a guide when choosing the solvent for MALDI sample preparation. The highest intensity PVAc signals were obtained when ethyl acetate was used as a solvent along with the lowest matrix–analyte ratio (2,5-dihydroxybenzoic acid was used as a matrix in all experiments). The structure of the PVAc was established with high accuracy using the matrix-assisted laser desorption/ionization-Fourier transform mass spectrometry (MALDI-FTMS) analysis. It was demonstrated that PVAc undergoes unimolecular decomposition by losing acetic acid molecules from its backbone under the conditions of FTMS measurements. Number and weight average molecular weights as well as polydispersity indices were determined with both MALDI-TOF and MALDI-FTMS methods. The sample preparation protocol developed was applied to the analysis of a chewing gum and the molecular weight and structure of the polyvinyl acetate present in the sample were established. Thus, it was shown that optimized MALDI mass spectrometry could be used successfully for characterization of polyvinyl acetate in commercially available chewing gum.     

Experimental designs characterizing seasonal variations and solvent effects on the quantities of coumarin and related metabolites from Mikania laevigata

Statistical design mixtures of acetone, chloroform, dichloromethane and ethanol were used to study the effects of different solvents and their mixtures on the quantities of coumarin and related metabolites extracted from Mikania laevigata samples harvested in each of the four seasons. RP-HPLC-DAD and both positive and negative modes of UPLC-MS analyses were used to determine relative quantities of coumarin, o-coumaric acid and melilotic acids in each season for all the mixture design extracts. The existence and measurement of the relative abundances of melilotic acid in Mikania laevigata have not been reported previously. Highest coumarin concentrations were encountered in the summer whereas its o-coumaric acid precursor and melilotic acid were most abundant in the spring. O-coumaric and melilotic acids concentrations were strongly correlated during the year. Also solvent effects were seen to be significant. Ethanol and 1:1 binary mixtures of ethanol and acetone extracted the largest quantities of coumarin whereas ethanolic binary and ternary mixtures with chloroform and dichloromethane provided the best yields of o-coumaric and melilotic acids. Statistical mixture models indicated that synergic binary interactions, especially those involving ethanol with acetone or chloroform, are important in the Mikania extraction process.     

Estimation of rotation ambiguity in multivariate curve resolution with charged particle swarm optimization (cPSO‐MCR)

Rotation ambiguity (RA) in multivariate curve resolution (MCR) is an undesirable case, when the physicochemical constraints are not sufficiently strong to provide a unique resolution of the data matrix of the mixtures into spectra and concentration profiles of individual chemical components. RA is often met in MCR of overlapped chromatographic peaks, kinetic and equilibrium data, and fluorescence two‐dimensional spectra. In case of RA, a single candidate solution has little practical value. So, the whole set of feasible solutions should be characterized somehow. It is a quite intricate task in a general case. In the present paper, a method was proposed to estimate RA with charged particle swarm optimization (cPSO), a population‐based algorithm. The criteria for updating the particles were modified, so that the swarm converged to the steady state, which spanned the set of feasible solutions. The performance of cPSO‐MCR was demonstrated on test functions, simulated datasets, and real‐world data. Good accordance of the cPSO‐MCR results with the analytical solutions (Borgen plots) was observed. cPSO‐MCR was also shown to be capable of estimating the strength of the constraints and of revealing RA in noisy data. As compared with analytical methods, cPSO‐MCR is simpler to implement, expands to more than three chemical compounds, is immune to noise, and can be easily adapted to virtually all types of constraints and objective functions (constraint based or residue based). cPSO‐MCR also provides natural visual information about the level of RA in spectra and concentration profiles, similar to the methods of two extreme solutions (e.g., MCR‐BANDS). Copyright © 2014 John Wiley & Sons, Ltd.     

维布妥昔单抗关键中间体的合成工艺优化

本研究对维布妥昔单抗关键中间体(1)的合成工艺进行了改进与优化。以芴甲氧羰基-L-缬氨酸琥珀酰亚胺酯(2)为起始原料,先后经酯的氨解反应、酰胺化、Fmoc脱保护、酰胺化与酯交换反应制得目标产品1,总收率11.6%,纯度99.2%,产物结构经1H NMR, 13C NMR和HRMS表征。优化后的工艺路线具有反应条件温和、可操作性强、生产过程更安全的特点。在初步放大试验中,首步投料量达百克级别,并已完成三批工艺验证,适合于工业化生产。