Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: nonlinear constrained optimization

Sortuj według:

Ogranicz wyniki do:

An optimal design of micro-drill from the aspect of vibration analysis

Hoang T.-D., Nguyen D.-T.

Computer Assisted Methods in Engineering and Science

2016

Vol. 23, no. 4

191--204

This paper presents an approach to optimize the structure of a micro-drill for reducing its lateral vibration,which has a strong effect on the quality of drilled holes during the cutting process. The micro-drill and thespindle of a micro-drilling spindle system are modeled as Timoshenko’s beam elements. Each element withfive degrees of freedom at each node comprehensively includes the effects of continuous mass eccentricity,shear deformation, gyroscopic moments, rotational inertia with external thrust force and torque, andcoupling torsional and lateral effect. The finite element method is used to determine the lateral amplituderesponse at the micro-drill point, which is considering the objective function during the optimizationof the micro-drill by the interior-point approach. The diameters and the lengths of drill segments arechosen as the design variables with nonlinear constraints in the constant mass, mass center location, andtorsional deformation of the drill. The in-house finite element code-integrated optimization environmentis implemented in MATLAB to solve the optimal problem. The results showed that compared with theoriginal micro-drill, the lateral amplitude response at the drill point of the optimal one is reduced by 91.89% at an operating speed of 50 000 rounds per minute (r/min), and its first critical speed and thecorresponding amplitude response exceed those of the original one.

Derivative-free nonlinear optimization filter simplex

Correia A., Matias J., Mestre P., Serodio C.

International Journal of Applied Mathematics and Computer Science

2010

Vol. 20, no 4

679-688

The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.