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Optimization of Castings by using Surrogate Models
Linköping University, Department of Management and Engineering.
2007 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis structural optimization of castings and thermomechanical analysis of castings are studied.

In paper I an optimization algorithm is created by using Matlab. The algorithm is linked to the commercial FE solver Abaqus by using Python script. The optimization algorithm uses the successive response surfaces methodology (SRSM) to create global response surfaces. It is shown that including residual stresses in structural optimization of castings yields an optimal shape that differs significantly from the one obtained when residual stresses are excluded.

In paper II the optimization algorithm is expanded to using neural networks. It is tested on some typical bench mark problems and shows very promising results. Combining paper I and II the response surfaces can be either analytical functions, both linear and non-linear, or neural networks. The optimization is then performed by using sequential linear programming or by using a zero-order method called Complex. This is all gathered in a package called StuG-OPT.

In paper III and IV focus is on the thermomechanical problem when residual stresses are calculated. In paper III a literature review is performed and some numerical simulations are performed to see where numerical simulations can be used in the industry today. In paper IV simulations are compared to real tests. Several stress lattices are casted and the residual stresses are measured. Simulations are performed by using Magmasoft and Abaqus. In Magmasoft a J2-plasticity model is used and in Abaqus two simulations are performed using either J2-plasticity or the ”Cast Iron Plasticity” available in Abaqus that takes into account the different behavior in tension and compression for grey cast iron.

Place, publisher, year, edition, pages
Institutionen för ekonomisk och industriell utveckling, Linköpings universitet , 2007. , 23 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1325
Keyword [en]
Response Surface Methodology (RSM), Residual Stresses, Castings
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-10192ISBN: 978-91-85831-25-8 (print)OAI: oai:DiVA.org:liu-10192DiVA: diva2:16948
Presentation
2007-10-19, E1405, Hus E, Tekniska Högskolan i Jönköping, Jönköping, 10:00 (English)
Opponent
Supervisors
Note

Report code: LIU-TEK-LIC-2007:34.

Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2012-08-24
List of papers
1. Shape Optimization of Castings by using Successive Response Surface Methodology
Open this publication in new window or tab >>Shape Optimization of Castings by using Successive Response Surface Methodology
2008 (English)In: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 35, no 1, 11-28 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, an optimization routine for a thermomechanical problem is presented. The optimization routine is based on the successive response surface methodology where the panning and zooming technique presented by Stander and Craig has been implemented and improved. The optimization routine has been applied to an optimization problem of a three-dimensional beam that undergoes a solidification process. The material in the beam is assumed to be low-alloyed gray iron. The thermomechanical solidification analysis is uncoupled where, first, a thermal analysis is performed to determine the thermal history. This thermal history is then used to calculate the residual stresses in the beam. The residual stresses are solved by using classical J 2-plasticity with temperature-dependent material properties. The residual stresses from solidification are then carried on to the structural analysis where a mechanical load is applied. These are all linked together via scripts, and the commercial FE software Abaqus is used as the FE solver. The obtained maximum von Mises stress and mass information for every set of parameters are then exported to Matlab where general quadratic response surfaces are fitted by a least square method. Taken together, these response surfaces define a minimum of weight problem, which is solved by using sequential linear programming. To minimize the number of evaluations needed, the parameters are chosen to be D-optimally selected. The numerical results show that the residual stresses from solidification might influence the optimal shape significantly. The residual stress results have been compared with those obtained from casting simulation softwares, and the results are similar. The optimization has been compared with a commercial optimization software and shows very promising results.

Keyword
Thermomechanical, Residual stresses, Optimization, Castings, Successive response surface methodology (SRSM)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12735 (URN)10.1007/s00158-007-0114-6 (DOI)
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2017-12-14
2. Successive Response Surface Methodology by using Neural Networks
Open this publication in new window or tab >>Successive Response Surface Methodology by using Neural Networks
2007 (English)In: Proceedings of 7th World Congress on Structural and Multidisciplinary Optimization, Seoul, Korea, 2007Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12736 (URN)
Available from: 2007-11-07 Created: 2007-11-07
3. Residual Stresses in Castings
Open this publication in new window or tab >>Residual Stresses in Castings
Manuscript (Other academic)
Identifiers
urn:nbn:se:liu:diva-12737 (URN)
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2010-01-13
4. Simulation and Measurement of Residual Stresses in a Stress Lattice
Open this publication in new window or tab >>Simulation and Measurement of Residual Stresses in a Stress Lattice
2007 (English)In: Proceedings of 2nd International Conference on Simulation and Modelling of Metallurgical Processes in Steelmaking,, 2007Conference paper, Published paper (Refereed)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12738 (URN)
Available from: 2007-11-07 Created: 2007-11-07

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Gustafsson, Erik

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