飞机疲劳试验工程优化方法

相关系数法是一种有效的飞机疲劳试验载荷处理方法。通过对某型飞机后机身设计弯矩图和试验弯矩图的比较 。

An Improved Differential Evolution for Optimization of Chemical Process

Differential evolution （DE） is an evolutionary optimization method, which has been successfully used in many practical cases. However, DE involves large computation time, especially, when used to optimize the compurationally expensive objective function. To overcome this .difficulty, the concept of immunity based on vaccination is used to help proliferate excellent schemata and to restrain the degenerate phenomenon. To improve the effective- ness of vaccines, a new vaccine autonomous obtaining method, and a method of deciding the probability of vacci- nation are proposed. In addition, a method for modifying the search space dynamically is proposed to enhance the possibility of converging to the true global optimum. Experiments showed that the improved DE performs better than the classical DE significantly.

A Genetic Fuzzy Analytical Hierarchy Process Based Projection Pursuit Method for Selecting Schemes of Water Transportation Projects

The optimal selection of schemes of water transportation projects is a process of choosing a relatively optimal scheme from a number of schemes of water transportation programming and management projects, which is of importance in both theory and practice in water resource systems engineering. In order to achieve consistency and eliminate the dimensions of fuzzy qualitative and fuzzy quantitative evaluation indexes, to determine the weights of the indexes objectively, and to increase the differences among the comprehensive evaluation index values of water transportation project schemes, a projection pursuit method, named FPRM-PP for short, was developed in this work for selecting the optimal water transportation project scheme based on the fuzzy preference relation matrix. The research results show that FPRM-PP is intuitive and practical, the correction range of the fuzzy rained is both stable and accurate; preference relation matrix A it produces is relatively small, and the result obtherefore FPRM-PP can be widely used in the optimal selection of different multi-factor decision-making schemes.

Improved Hybrid Differential Evolution-Estimation of Distribution Algorithm with Feasibility Rules for NLP/MINLP Engineering Optimization Problems

In this paper, an improved hybrid differential evolution-estimation of distribution algorithm (IHDE-EDA) is proposed for nonlinear programming (NLP) and mixed integer nonlinear programming (MINLP) models in engineering optimization fields. In order to improve the global searching ability and convergence speed, IHDE-EDA takes full advantage of differential information and global statistical information extracted respectively from differential evolution algorithm and annealing mechanism-embedded estimation of distribution algorithm. Moreover, the feasibility rules are used to handle constraints, which do not require additional parameters and can guide the population to the feasible region quickly. The effectiveness of hybridization mechanism of IHDE-EDA is first discussed, and then simulation and comparison based on three benchmark problems demonstrate the efficiency, accuracy and robustness of IHDE-EDA. Finally, optimization on an industrial-size scheduling of two-pipeline crude oil blending problem shows the practical applicability of IHDE-EDA.

Chemical process dynamic optimization based on hybrid differential evolution algorithm integrated with Alopex

To solve dynamic optimization problem of chemical process (CPDOP), a hybrid differential evolution algorithm, which is integrated with Alopex and named as Alopex-DE, was proposed. In Alopex-DE, each original individual has its own symbiotic individual, which consists of control parameters. Differential evolution operator is applied for the original individuals to search the global optimization solution. Alopex algorithm is used to co-evolve the symbiotic individuals during the original individual evolution and enhance the fitness of the original individuals. Thus, control parameters are self-adaptively adjusted by Alopex to obtain the real-time optimum values for the original population. To illustrate the whole performance of Alopex-DE, several varietal DEs were applied to optimize 13 benchmark functions. The results show that the whole performance of Alopex-DE is the best. Further, Alopex-DE was applied to solve 4 typical CPDOPs, and the effect of the discrete time degree on the optimization solution was analyzed. The satisfactory result is obtained.

Modified Augmented Lagrange Multiplier Methods for Large-Scale Chemical Process Optimization

Chemical process optimization can be described as large-scale nonlinear constrained minimization. The modified augmented Lagrange multiplier methods (MALMM) for large-scale nonlinear constrained minimization are studied in this paper. The Lagrange function contains the penalty terms on equality and inequality constraints and the methods can be applied to solve a series of bound constrained sub-problems instead of a series of unconstrained sub-problems. The steps of the methods are examined in full detail. Numerical experiments are made for a variety of problems, from small to very large-scale, which show the stability and effectiveness of the methods in large-scale problems.

Engineering Design Optimization Based on Intelligent Response Surface Methodology

An intelligent response surface methodology (IRSM) was proposed to achieve the most competitive metal forming products, in which artificial intelligence technologies are introduced into the optimization process. It is used as simple and inexpensive replacement for computationally expensive simulation model. In IRSM, the optimal design space can be reduced greatly without any prior information about function distribution. Also, by identifying the approximation error region, new design points can be supplemented correspondingly to improve the response surface model effectively. The procedure is iterated until the accuracy reaches the desired threshold value. Thus, the global optimization can be performed based on this substitute model. Finally, we present an optimization design example about roll forming of a "U" channel product.

Stability analysis of underground engineering based on multidisciplinary design optimization

Aiming at characteristics of underground engineering,analyzed the feasibility of Multidisciplinary Design Optimization (MDO) used in underground engineering,and put forward a modularization-based MDO method and the idea of MDO to resolve problems in stability analysis,proving the validity and feasibility of using MDO in underground engi- neering.Characteristics of uncertainty,complexity and nonlinear become bottle-neck to carry on underground engineering stability analysis by MDO.Therefore,the application of MDO in underground engineering stability analysis is still at a stage of exploration,which need some deep research.

Analysis of Cutting Force by End Milling Using Artificial ntelligence

The cutting forces during end milling process by using Genetic Algorithm are investigated in this paper. However, automated CNC （computer numerical control） programming by milling machine is intended to use for special required conditions of programming of tool path length, and analysis of cutting force and optimization of main parameters are presented. Some effective simplification of automated programming is done for cutting force. The cutting force is modelled and analyzed into mathematical simulations in order to optimize the main cutting parameters, also in this case tool path length, it is get as free trajectory. Optimization is carried out by using the Matlab/Genetic Algorithm method that excessively reduce the time and to optimize the main cutting parameters of machining. The number of experiments, measurements and results of cutting force （F~）, are presented in 3D as well as in tables. In order to verify the accuracy of the 3 D simulation with optimization method, the results are compared in experimental and theoretical way. In other word, these results indicate directly that the optimized parameters are capable of machining the workpiece. Achieved results that are presented in this paper may in general help the new researcher as well as manufacturing industries of metal cutting.

Conceptual Framework for an Integrated Method to Optimize Sustainability of Engineering Systems

It is necessary to change the current dynamic of growth, to assure that future generations can satisfy their needs. Sustainable development and global sustainability are two concepts that have achieved great importance in almost every sector of activity. There is a wide range of methods and models for sustainability assessment. Nevertheless, it is necessary to go beyond evaluation, looking for sustainability optimization. In spite of this, little work has been done on the latter field. The authors present here a conceptual proposal for an integrated method to optimize sustainability of engineering systems, based on the MIVES （integrated value method for evaluating sustainability） method. For a better understanding of the method, its essential steps for optimizing an energy sub-system are summarized （shell-and-tube heat exchanger）.

合成生物系统的组合优化

合成生物学所面临的一项重要挑战是构建具有全新功能的生物系统。由于生物系统固有的复杂性,仅通过理性设计,通常难以使合成基因线路发挥出最优的功能。组合工程的兴起和发展为获得组合优化性状提供了有利条件,并大大促进了具有全新功能的生物系统的构建。文中主要从单个元件的微调、代谢通路的优化以及基因组范围内靶点的识别和组合修饰三个方面入手,总结和评述了近些年表现突出的合成生物系统的组合优化方法。

A survey of numerical algorithms for trajectory optimization of flight vehicles

As one of the important components of computational flight mechanics and control,numerical algorithms of trajectory optimization for flight vehicles are currently studied by many researchers in aerospace engineering to completely solve these difficult problems,but few papers on the survey of this research field have been published recently.Based on the investigation of more than one hundred literatures,considering the application perspectives of computational flight mechanics and recent developments of trajectory optimization,the numerical algorithms of trajectory optimizations for aerospace vehicles are summarized and systematically analyzed.This paper summarized the basic principle,characteristics and application for all kinds of current trajectory optimization algorithms;and introduced some new methods and theories appearing in recent years.Finally,collaborative trajectory optimization for many flight vehicles,and hypersonic vehicle trajectory optimization were mainly reviewed in this paper.In the conclusion of this paper,the future research properties are presented regarding to numerical algorithms of trajectory optimization and control for flight vehicles as follows:collaboration and antagonization for many flight vehicles and multiple targets,global,real-time online,high accuracy of 7-D trajectory,considering all kinds of unknown random disturbances in trajectory optimization,and so on.

Multi-objective optimization of the streamlined head of high-speed trains based on the Kriging model

As the running speed of high-speed trains increases, aerodynamic drag becomes the key factor which limits the further increase of the running speed and energy consumption. Aerodynamic lift of the trailing car also becomes the key force which affects the amenity and safety of the train. In the present paper, a simplified CRH380A high-speed train with three carriages is chosen as the model in order to optimize aerodynamic drag of the total train and aerodynamic lift of the trailing car. A constrained mul- ti-objective optimization design of the aerodynamic head shape of high-speed trains based on adaptive non-dominated sorting genetic algorithm is also developed combining local function three-dimensional parametric approach and central Latin hypercube sampling method with maximin criteria based on the iterative local search algorithm. The results show that local function parametric approach can be well applied to optimal design of complex three-dimensional aerodynamic shape, and the adaptive non-dominated sorting genetic algorithm can be more accurate and efficient to find the Pareto front. After optimization the aerodynamic drag of the simplified train with three carriages is reduced by 3.2%, and the lift coefficient of the trailing car by 8.24%, the volume of the streamlined head by 2.16%; the aerodynamic drag of the real prototype CRH380A is reduced by 2.26%, lift coefficient of the trailing car by 19.67%. The variation of aerodynamic performance between the simplified train and the true train is mainly concentrated in the deformation region of the nose cone and tail cone. The optimization approach proposed in the present paper is simple yet efficient, and sheds lights on the constrained multi-objective engineering optimization design of aerodynamic shape of high-speed trains.