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Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering

A. Andrade-Campos
Copyright: © 2013 |Pages: 24
ISBN13: 9781466618671|ISBN10: 1466618671|EISBN13: 9781466618688
DOI: 10.4018/978-1-4666-1867-1.ch001
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MLA

Andrade-Campos, A. "Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering." Dynamic Methods and Process Advancements in Mechanical, Manufacturing, and Materials Engineering, edited by J. Paulo Davim, IGI Global, 2013, pp. 1-24. https://doi.org/10.4018/978-1-4666-1867-1.ch001

APA

Andrade-Campos, A. (2013). Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering. In J. Davim (Ed.), Dynamic Methods and Process Advancements in Mechanical, Manufacturing, and Materials Engineering (pp. 1-24). IGI Global. https://doi.org/10.4018/978-1-4666-1867-1.ch001

Chicago

Andrade-Campos, A. "Development of an Optimization Framework for Parameter Identification and Shape Optimization Problems in Engineering." In Dynamic Methods and Process Advancements in Mechanical, Manufacturing, and Materials Engineering, edited by J. Paulo Davim, 1-24. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-1867-1.ch001

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Abstract

The use of optimization methods in engineering is increasing. Process and product optimization, inverse problems, shape optimization, and topology optimization are frequent problems both in industry and science communities. In this paper, an optimization framework for engineering inverse problems such as the parameter identification and the shape optimization problems is presented. It inherits the large experience gain in such problems by the SiDoLo code and adds the latest developments in direct search optimization algorithms. User subroutines in Sdl allow the program to be customized for particular applications. Several applications in parameter identification and shape optimization topics using Sdl Lab are presented. The use of commercial and non-commercial (in-house) Finite Element Method codes to evaluate the objective function can be achieved using the interfaces pre-developed in Sdl Lab. The shape optimization problem of the determination of the initial geometry of a blank on a deep drawing square cup problem is analysed and discussed. The main goal of this problem is to determine the optimum shape of the initial blank in order to save latter trimming operations and costs.

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