Improved Parallel Preconditioners for Multidisciplinary Topology Optimisations

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Date

2016

Authors

Akay, H. U.
Akay, Hasan Umur
Oktay, E.
Manguoglu, M.
Sivas, A. A.

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Taylor & Francis Ltd

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Automotive Engineering
(2009)
Having started education in 2009, the Atılım university Department of Automotive Engineering offers an academic environment at international standards, with its education in English, a contemporary curriculum and ever-better and ever-developing laboratory opportunities. In addition to undergraduate degree education, the graduate program of multi-disciplinary mechanical engineering offers the opportunity for graduate and doctorate degree education automotive engineering. The Atılım University Automotive Engineering has been selected to be the best in Turkey in 2020 in the field of automotive engineering with studies in energy efficiency, motor performance, active/ passive automotive security and vehicle dynamics conducted in the already-existing laboratories of its own. Our graduates are employed at large-scale companies that operate in Turkey, such as Isuzu, Ford Otosan, Hattat, Honda, Hyundai, Karsan, Man, Mercedes-Benz, Otokar, Renault, Temsa, Tofaş, Toyota, Türk Traktör, Volkswagen (to start operation in 2020). In addition, our graduates have been hired at institutions such as Tübitak, Tai, Aselsan, FNSS, Ministry of National Defence, Tcdd etc. or at supplier industries in Turkey. Due to the recent evolution undergone by the automotive industry with the development of electric, hybrid and autonomous vehicle technologies, automotive engineering has gained popularity, and is becoming ever more exhilarating. In addition to combustion engine technologies, our students also gain expertise in these fields. The “Formula Student Car” contest organized since 2011 by the Society of Automotive Engineers (SAE) where our Department ranked third globally in 2016 is one of the top projects conducted by our department where we value hands-on training. Our curriculum, updated in 2020, focuses on computer calculation and simulation courses, as well as laboratory practice, catered to modern automotive technologies.

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Abstract

Two commonly used preconditioners were evaluated for parallel solution of linear systems of equations with high condition numbers. The test cases were derived from topology optimisation applications in multiple disciplines, where the material distribution finite element methods were used. Because in this optimisation method, the equations rapidly become ill-conditioned due to disappearance of large number of elements from the design space as the optimisations progresses, it is shown that the choice for a suitable preconditioner becomes very crucial. In an earlier work the conjugate gradient (CG) method with a Block-Jacobi preconditioner was used, in which the number of CG iterations increased rapidly with the increasing number processors. Consequently, the parallel scalability of the method deteriorated fast due to the increasing loss of interprocessor information among the increased number of processors. By replacing the Block-Jacobi preconditioner with a sparse approximate inverse preconditioner, it is shown that the number of iterations to converge became independent of the number of processors. Therefore, the parallel scalability is improved.

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Akay, Hasan U/0000-0003-2574-9942; Sivas, Abdullah Ali/0000-0002-5263-1889

Keywords

Topology optimisation, parallel methods, parallel scalability, iterative solvers, preconditioners, conjugate gradient, Block-Jacobi, sparse approximate inverse

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0

WoS Q

Q4

Scopus Q

Q3

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Volume

30

Issue

4

Start Page

329

End Page

336

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