Papers by Keyword: Nonlinear Optimization

Abstract: Today, artificial implants (AI) industry depends strongly on tribological constitution of the material (s) of the implant. Erosion, corrosion, tribocorrosion and biocorrosion are essential factors to determine both functionality and lifetime of the AIs. Histo-Biocompatibility is also an additional constraint, indispensable for implant manufacturing process. The prediction of durability, based on the computational and experimental study of constituents of AI material (s) are key factors to obtain objective data of any AI characteristics. This contribution deals with a computational comparative analysis of materials for hip implants using Archard’s model mainly. Selected hip implant material hardness are Co-Cr alloy and Titanium types. Method is carried out with specific material data, e.g., hardness or wear constants, nonlinear optimization and graphical subroutines. Results presented are both numerical and graphical. Particular interest is focused on application of the 3D Graphical Optimization method.

Abstract: In this paper the technique of parameter identification is investigated to reconstruct the 3D transient temperature field for the simulation of laser beam welding. The reconstruction bases on volume heat source models and makes use of experimental data. The parameter identification leads to an inverse heat conduction problem which cannot be solved exactly but in terms of an optimal alignment of the simulation and experimental data. To solve the inverse problem, methods of nonlinear optimization are applied to minimize a problem dependent objective function.In particular the objective function is generated based on the Response Surface Model (RSM) technique. Sampling points on the RSM are determined by means of Finite-Element-Analysis (FEA). The scope of this research paper is the evaluation and comparison of gradient based and stochastic optimization algorithms. The proposed parameter identification makes it possible to determine the heat source model parameters in an automated way. The methodology is applied on welds of dissimilar material joints.

Abstract: A serial link manipulator consist of various unbalanced bars (links) attached by torsional joints that are subjected to torque loads due to the weight and configuration of the manipulator. This paper proposes a solution to passive weight compensation for serial link manipulators, using torsional springs. A set of characteristic points is selected and evaluated through sensibility analysis to define the required maneuvers. A nonlinear optimization methodology is used to find the springs parameters to minimize the energy consumption during the execution of the defined maneuvers. The energy saving is estimated through simulation as well as the effect of the maximum preload allowed for the spring.