Optimization Methods Applied to Selecting Support Positions in Fixture Design

1991 ◽  
Vol 113 (4) ◽  
pp. 412-418 ◽  
Author(s):  
R. J. Menassa ◽  
W. R. DeVries

This paper proposes optimization techniques to assist in the design and evaluation of fixtures for holding prismatic workpieces. This formulation of the fixturing design problem takes into account deflection of the workpiece subjected to assembly or machining loads. Using the minimization of the workpiece deflection at selected points as the design criterion, the design problem is determining the positions of the fixture supports. The Finite Element Method is used for calculating deflections that are the basis for the design objective function, and the Broyden-Fletcher-Goldfarb-Shanno optimization algorithm is used to determine the fixture support positions. In this paper the proposed objective function is developed and the method is illustrated with three numerical examples.

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Li Tian ◽  
Dai Xiaoxia ◽  
Zhang Chengwei

We propose two algorithms for elliptic boundary value problems in shape optimization. With the finite element method, the optimization problem is replaced by a discrete variational problem. We give rules and use them to decide which elements are to be reserved. Those rules are determined by the optimization; as a result, we get the optimal design in shape. Numerical examples are provided to show the effectiveness of our algorithms.


1975 ◽  
Vol 97 (2) ◽  
pp. 520-526 ◽  
Author(s):  
N. M. Sevak ◽  
C. W. McLarnan

Flexible link mechanisms (commonly referred to as flexural mechanisms) subjected to large static deflections are analyzed and synthesized for function generation. The large deflections present nonlinear problems. The nonlinear analysis is performed by the finite element method with aid of Martin’s linear incremental procedure and the synthesis problems are solved by the optimization techniques of Fletcher and Powell’s variable metric method. The techniques are demonstrated on mechanisms in which one or two links are flexible. The obtained analytical results are verified experimentally.


Author(s):  
Soroosh Hassanpour ◽  
G. R. Heppler

The development of a simplified micropolar beam model is presented and the governing dynamic equations for a micropolar beam deforming in 3D space, under different types of external loading and boundary conditions are derived. The dynamic equations are derived from Hamilton’s principle and the finite element method is used to provide numerical examples. The modal behavior of the developed micropolar beam model and the conditions under which the results of classical beam models will be recovered are presented.


The paper begins by noting that the practical and efficient numerical analysis of thin walled shells is far from a reality. Groundwork for the investigation starts with an examination of existing sufficiency conditions for convergence of the finite element method of analysis with refinement of mesh size; new and more practical conditions are then given specifically for shells. Working formulae of a suitable first approximation theory for the linear small deflexion behaviour are then given for arbitrary shells in lines of curvature and in geodesic coordinates. A variational principle is introduced which is more general than that for the well known assumed stress hybrid finite element model; its purpose is to provide a means to overcome the excessive rank deficiency which is sometimes encountered in the derive element stiffness matrix. , The formulae are next specialized to general developable shells for they are tne simplest to analyse and frequently occur in technology. Emphasis is given to the derivation of general formulae governing inextensional deformation, membrane action and rigid body movement because these constitute important factors in any adequate numerical analysis. . . , Specific application is made to circular cylindrical shells by first considering the interpolation of the kinematic continuity conditions along an arbitrary geodesic line. Details and numerical examples are provided for the first known fully compatible lines of curvature rectangular finite element which directly recovers arbitrary rigid body movements as well as inextensional deformations and membrane actions. The paper concludes with details and numerical examples of an arbitrarily shaped triangular finite element which employs the above mentioned variational principle m conjunction with linearly varying stress fields. All the rigid body movements are directly recovered as well as inextensional deformations and membrane actions. It is anticipated that this finite element and its derivatives will find widespread application.


2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
D. A. León-Velasco ◽  
M. M. Morín-Castillo ◽  
J. J. Oliveros-Oliveros ◽  
T. Pérez-Becerra ◽  
J. A. Escamilla-Reyna

In this work, the Finite Element Method is used for finding the numerical solution of an elliptic problem with Henstock–Kurzweil integrable functions. In particular, Henstock–Kurzweil high oscillatory functions were considered. The weak formulation of the problem leads to integrals that are calculated using some special quadratures. Definitions and theorems were used to guarantee the existence of the integrals that appear in the weak formulation. This allowed us to apply the above formulation for the type of slope bounded variation functions. Numerical examples were developed to illustrate the ideas presented in this article.


2012 ◽  
Vol 60 (2) ◽  
pp. 241-246 ◽  
Author(s):  
M. Szczepanik ◽  
T. Burczyński

Abstract. The paper is devoted to the application of the swarm methods and the finite element method to optimization of the stiffeners location in the 2-D structures (plane stress, bending plates and shells). The structures are optimized for the stress and displacement criteria. The numerical examples demonstrate that the method based on the swarm computation is an effective technique for solving the computer aided optimal design. The additional comparisons of the effectiveness of the particle swarm optimizer (PSO) and evolutionary algorithms (EA) are presented.


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