Pneumatic resistance network analysis and dimension optimization of high pressure electronic pneumatic pressure reducing valve

The structure and working principle of a self-deigned high pressure electronic pneumatic pressure reducing valve (EPPRV) with slide pilot are introduced.The resistance value formulas and the relationship between the resistance and pressure of three typical pneumatic resistances are obtained.Then,the method of static characteristics analysis only considering pneumatic resistances is proposed,the resistance network from gas supply to load is built up,and the mathematical model is derived from the flow rate formulas and flow conservation equations,with the compressibility of high pressure gas and temperature drop during the expansion considered in the model.Finally,the pilot spool displacement of 1.5 mm at an output pressure of 15MPa and the enlarging operating stroke of the pilot spool are taken as optimization targets,and the optimization is carried out based on genetic algorithm and the model mentioned above.The results show that the static characteristics of the EPPRV are significantly improved.The idea of static characteristics analysis and optimization based on pneumatic resistance network is valuable for the design of pneumatic components or system.

Optimal Design of a Main Driving Mechanism for Servo Punch Press Based on Performance Atlases

The servomotor drive turret punch press is attracting more attentions and being developed more intensively due to the advantages of high speed,high accuracy,high flexibility,high productivity,low noise,cleaning and energy saving.To effectively improve the performance and lower the cost,it is necessary to develop new mechanisms and establish corresponding optimal design method with uniform performance indices.A new patented main driving mechanism and a new optimal design method are proposed.In the optimal design,the performance indices,i.e.,the local motion/force transmission indices ITI,OTI,good transmission workspace good transmission workspace(GTW) and the global transmission indices GTIs are defined.The non-dimensional normalization method is used to get all feasible solutions in dimensional synthesis.Thereafter,the performance atlases,which can present all possible design solutions,are depicted.As a result,the feasible solution of the mechanism with good motion/force transmission performance is obtained.And the solution can be flexibly adjusted by designer according to the practical design requirements.The proposed mechanism is original,and the presented design method provides a feasible solution to the optimal design of the main driving mechanism for servo punch press.

STRATA AND SURFACE SUBSIDENCE CONTROL IN STRIP-PARTIAL MINING UNDER BUILDINGS

This paper systematiedy expounds the history and present situation of tbe research &application of strip-parttal mining at home and abroad. Tbe prospect of using strip-parttal miningmcthod to mine under balldings (structures) at the present situation of market economy is also expounded here Strata & surface subsidence mechanism of atrip-partni mining the optimization ofthe width of unit goaf & coal pillar as well as the calculation method of surface subsidence pridictionbased on Holding-Ptate Control Theory and Coal Pillar Long-term Stability, which are our researchachivements in recent years about strata & surface subsidence control in strip-partial mining, arethe main points introdued bere.

Aerodynamic multi-objective integrated optimization based on principal component analysis

Based on improved multi-objective particle swarm optimization（MOPSO） algorithm with principal component analysis（PCA） methodology, an efficient high-dimension multiobjective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency,the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil,and the proposed method is integrated into aircraft multi-disciplinary design（AMDEsign） platform, which contains aerodynamics, stealth and structure weight analysis and optimization module.Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.

Variable-fidelity optimization with design space reduction

Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.

Structural dimension optimization and mechanical response analysis of fabricated honeycomb plastic pavement slab

Because of favorable mechanical properties,deformation resistance and being conducive to environmental protection,honeycomb fabricated plastic pavement slabs are highly recommended these years.At present,most studies focus on the performance of plastic materials,however,the dimension optimization of fabricated plastic pavement slab is rarely mentioned.In this paper,an optimized geometry of the honeycomb pavement slab was determined through finite element analysis.Mechanical response of honeycomb slabs with different internal dimensions and external dimensions were explored.Several dimension factors were taken into consideration including the side length,rib thickness,the thickness of both top and bottom slabs of honeycomb structure and the length,the width and the thickness of the fabricated plastic slab.The results showed that honeycomb pavement slab with 6 cm bottom slab,12 cm top slab,18 cm side length and 6 cm rib thickness is recommended,additionally,an external dimension of 4 m×4 m×0.45 m is suggested.Then,the mechanical responses of this optimized fabricated plastic slab were further investigated.Significance of different influencing factors,including wheel load,elastic modulus of plastic material,base layer thickness,soil foundation modulus and base layer modulus were ranked.

MINIMUM PERIOD CONTROL PROBLEM FOR INFINITE DIMENSIONAL SYSTEM

In order to solve the so-called minimum period control problem for a class of abstract evolutionary systems, the authors study an infinite dimensional time optimal control problem with mixed type target set. To the latter problem complete results are established, which then are applied to the former to derive the desirable answer.

Penalty Algorithms in Hilbert Spaces

We analyze the classical penalty algorithm for nonlinear programming in Hilbert spaces and obtain global convergence results, as well as asymptotic superlinear convergence order. These convergence results generalize similar results obtained for finite-dimensional problems. Moreover, the nature of the algorithms allows us to solve the unconstrained subproblems in finite-dimensional spaces.

State Prediction of Chaotic System Based on ANN Model

The choice of time delay and embedding dimension is very important to the phase space reconstruction of any chaotic time series. In this paper, we determine optimal time delay by computing autocorrelation function of time series. Optimal embedding dimension is given by means of the relation between embedding dimension and correlation dimension of chaotic time series. Based on the methods above, we choose ANN model to appoximate the given true system. At the same time, a new algorithm is applied to determine the network weights. At the end of this paper, the theory above is demonstrated through the research of time series generated by Logistic map.