Concurrent shape and topology optimization for steady conjugate heat transfer

Makhija, David; Beran, Philip S.

doi:10.1007/s00158-018-2110-4

Cited by 14 publications

(6 citation statements)

References 55 publications

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“…In 2019, Pietropaoli et al [135] extended their previous work to three-dimensional internal coolant systems. Makhija and Beran [136] presented a concurrent optimisation method using a shape parametrisation for the external shape and a density-based parametrisation for the internal geometry. Subramaniam et al [137] investigated the inherent competition between heat transfer and pressure drop.…”

Section: Forced Convectionmentioning

confidence: 99%

A Review of Topology Optimisation for Fluid-Based Problems

Alexandersen

Andreasen

2020

Fluids

183

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This review paper provides an overview of the literature for topology optimisation of fluid-based problems, starting with the seminal works on the subject and ending with a snapshot of the state of the art of this rapidly developing field. “Fluid-based problems” are defined as problems where at least one governing equation for fluid flow is solved and the fluid–solid interface is optimised. In addition to fluid flow, any number of additional physics can be solved, such as species transport, heat transfer and mechanics. The review covers 186 papers from 2003 up to and including January 2020, which are sorted into five main groups: pure fluid flow; species transport; conjugate heat transfer; fluid–structure interaction; microstructure and porous media. Each paper is very briefly introduced in chronological order of publication. A quantititive analysis is presented with statistics covering the development of the field and presenting the distribution over subgroups. Recommendations for focus areas of future research are made based on the extensive literature review, the quantitative analysis, as well as the authors’ personal experience and opinions. Since the vast majority of papers treat steady-state laminar pure fluid flow, with no recent major advancements, it is recommended that future research focuses on more complex problems, e.g., transient and turbulent flow.

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Section: Forced Convectionmentioning

confidence: 99%

A Review of Topology Optimisation for Fluid-Based Problems

Alexandersen

Andreasen

2020

Fluids

183

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“…Thereafter, the above density-based representation with the different penalization functions, including SIMP and RAMP (rational approximation of material properties), etc., have been utilized in a wide range of single-flow HX problems [32]- [85]. Additionally, some other researchers [86]- [101] used an opposite representation of design parametrization by assigning γ = 1 for the solid phase or non-existing fluid phase and γ = 0 for the fluid phase. Note that no evidence demonstrates that such different representation of solid and liquid phases will significantly affect the solutions or efficiency of TO in the single-flow heat transfer problems.…”

Section: Density-based Methodsmentioning

confidence: 99%

“…[59]- [62], [64]- [78], [80], [82]- [84], [86], [89], [91], [94]- [100], [103]- [105], [116]- [119], [121], [122], [136]- [138]. As for the single-flow HXs, for instance, Dede et al…”

Section: Finite Element Methods (Fem)mentioning

confidence: 99%

Topology optimization of heat exchangers: A review

Fawaz

Younan

Corre

et al. 2022

Energy

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“…to account for the solvers, the necessary transfer routines between them, and FSI mesh deformations. For a pure CHT problem, another approach using a residual-based formulation for the PDE solvers and subsequent derivation of the discrete adjoint equations is presented in Makhija and Beran (2019), it also incorporates density-based topology optimization variables into the problem setting, which in the SU2 framework is only currently supported for FSI problems (Gomes and Palacios 2020). Indeed, the differentiation of multiphysics solvers for topology optimization is common (Dunning et al 2015;Lundgaard et al 2018;Picelli et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Discrete adjoint methodology for general multiphysics problems

Burghardt

Gomes

Kattmann

et al. 2022

Struct Multidisc Optim

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This article presents a methodology whereby adjoint solutions for partitioned multiphysics problems can be computed efficiently, in a way that is completely independent of the underlying physical sub-problems, the associated numerical solution methods, and the number and type of couplings between them. By applying the reverse mode of algorithmic differentiation to each discipline, and by using a specialized recording strategy, diagonal and cross terms can be evaluated individually, thereby allowing different solution methods for the generic coupled problem (for example block-Jacobi or block-Gauss-Seidel). Based on an implementation in the open-source multiphysics simulation and design software SU2, we demonstrate how the same algorithm can be applied for shape sensitivity analysis on a heat exchanger (conjugate heat transfer), a deforming wing (fluid–structure interaction), and a cooled turbine blade where both effects are simultaneously taken into account.

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Concurrent shape and topology optimization for steady conjugate heat transfer

Cited by 14 publications

References 55 publications

A Review of Topology Optimisation for Fluid-Based Problems

A Review of Topology Optimisation for Fluid-Based Problems

Topology optimization of heat exchangers: A review

Discrete adjoint methodology for general multiphysics problems

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