Automatic Parameter Classification for Dimension Reduction as Basis for Robust Parameter Identification

Daniela Steffes-Lai

doi:10.4028/www.scientific.net/KEM.611-612.1383

Paper Titles

Modelling of Inertia Friction Welding Using Finite Element Analysis and Computational Fluid Dynamics
p.1344

An Object-Oriented Analysis of Complex Numerical Models
p.1356

Methods for the Numerical Modelling of the Adhesive Interlayer of Sandwich-Sheets in Case of Coupled Thermo-Mechanical FE-Analysis
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Elastic-Plastic Reduced Order Modelling of Sheet and Profiles Bending-under-Tension
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Automatic Parameter Classification for Dimension Reduction as Basis for Robust Parameter Identification
p.1383

Data Exploration Approach Versus Sensitivity Analysis for Optimization of Metal Forming Processes
p.1390

Nickel Superalloy Components Surface Integrity Control through Numerical Optimization
p.1396

A Fast Approach to Shape Optimization Using the Inverse FEM
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Basic Investigations of Non-Pre-Punched Joining by Forming of Aluminium Alloy and High Strength Steel with Shear-Clinching Technology
p.1413

HomeKey Engineering MaterialsKey Engineering Materials Vols. 611-612Automatic Parameter Classification for Dimension...

Automatic Parameter Classification for Dimension Reduction as Basis for Robust Parameter Identification

Abstract:

This paper presents a fully automatic parameter classification procedure in order to identify the most influencing parameters together with locally interesting parts of the component considered in a certain processing step. The results of this classification approach are used for a parameter space reduction in order to minimize the computational effort for subsequent analysis and optimization tasks based on forecast models. In particular, an outlook on the evaluation of radial basis function metamodels for a robust parameter identification is given. We demonstrate the classification procedure and its benefits by an industrially relevant deep drawing process of a pan with secondary design elements.

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Periodical:

Key Engineering Materials (Volumes 611-612)

Pages:

1383-1389

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.611-612.1383

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Online since:

May 2014

Authors:

Daniela Steffes-Lai*

Keywords:

Deep Drawing, Parameter Classification, Parameter Uncertainty, Sensitivity Analysis

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