Large-scale topology optimization incorporating local-in-time adjoint-based method for unsteady thermal-fluid problem

Yaji, Kentaro; Ogino, Masao; Chen, Cong; Fujita, Kikuo

doi:10.1007/s00158-018-1922-6

Cited by 37 publications

(28 citation statements)

References 18 publications

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“…Sato et al [125] used an adaptive weighting scheme for the multiobjective topology optimisation of active heat sinks. Yaji et al [126] applied a local-in-time approximate transient adjoint method for topology optimisation of large scale problems with oscillating inlet flow. Haertel et al [127] presented a pseudo-3D model for extruded forced convection heat sinks, actually considering the chip temperature by coupling a thermofluid design layer to a conductive base plate layer.…”

Section: Forced Convectionmentioning

confidence: 99%

“…It is clear that FEM is the most widely used discretisation method with 134 papers or 76%. The next most used method is LBM at 28 papers [14,20,22,24,26,[36][37][38]44,55,65,69,75,77,78,84,97,108,113,118,119,126,131,163,168,172,173,186] or 16%. PM is the least used method with only a single paper [79].…”

Section: Design Representationsmentioning

confidence: 99%

“…For species transport, there are four papers [93,98,105,107]. For conjugate heat transfer, there are eight in forced convection [110,117,119,122,126,129,132,135] and six in natural convection [150,151,[153][154][155]160]. The fluid-structure interaction category counts four papers [164,168,172,173], but it must be noted that, common for all, the three-dimensional design freedom is severely limited, as the design domain is restricted in the third dimension.…”

Section: Three-dimensional Problemsmentioning

confidence: 99%

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A Review of Topology Optimisation for Fluid-Based Problems

Alexandersen

Andreasen

2020

Fluids

171

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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%

Section: Design Representationsmentioning

confidence: 99%

Section: Three-dimensional Problemsmentioning

confidence: 99%

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A Review of Topology Optimisation for Fluid-Based Problems

Alexandersen

Andreasen

2020

Fluids

171

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“…In contrast, the under-rib convection is strong in the interdigitated flow field and topology optimized flow field. Figure 5 shows that the value of objective function in the optimization problem described as (36), and overpotential in the topology optimized flow field and interdigitated flow filed indicate higher performance than those of the parallel flow field at constant pressure drop. Since the under-rib convection is weak in the parallel flow field, the value of objective function with the parallel flow field is the lowest.…”

Section: Effect Of Flow Field Designmentioning

confidence: 99%

“…For flow field design problems, Borrvall and Petersson [26] proposed a topology optimization method to minimize power dissipation in Stokes flow, and this has been expanded to laminar Navier-Stokes flow problems [27][28][29] and turbulence prob- lems [30,31]. The fluid topology optimization has been applied to multiphysics problems such as fluid-structure interaction problems [32,33], forced convection problems [34][35][36], natural convection problems [37][38][39] and turbulent heat transfer problems [40,41].…”

Section: Introductionmentioning

confidence: 99%

Computational design of flow fields for vanadium redox flow batteries via topology optimization

Chen

Yaji

Yamasaki

et al. 2019

Journal of Energy Storage

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Topology optimization of convective heat transfer by the lattice Boltzmann method

Luo

Chen

et al. 2022

Numerical Methods in Fluids

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Topology optimization (TO) is a dependable approach to obtain innovative designs with improved performance. This study presents a TO method based on the adjoint lattice Boltzmann method (ALBM) and the level set method which is developed for both one‐way coupled and two‐way coupled convective heat transfer problems. The adjoint lattice Boltzmann model for fully coupled natural convection system is derived, and the coupled solution strategy is applied in the ALBM. The forward model is validated by the finite element simulation, while the adjoint model and the sensitivity expression is validated by a finite difference check, and the whole TO method is validated by a typical pure fluid flow optimization problem given in the literature. The validated TO method is then applied to enhance the heat transfer of forced convection in a two‐dimensional open chamber, and the Pareto frontier of the bi‐objective optimization is further presented and the effects of the blockages at the inlet and outlet on the overall performance are revealed. Finally, the two‐dimensional natural convection process in a closed cavity is optimized, in which the effective heat transfer coefficient can be increased to 3.96 ∼ 6.11 times of that without the optimized design when the Grashof number ranges from 1.7 to 4.2 × 105. Moreover, effects of Grashof number, porosity limitation and solid thermal diffusivity on the optimization results are analyzed in detail. Physically reasonable designs are obtained for both forced convection and natural convection systems under various parameter settings, demonstrating the effectiveness and robustness of the presented TO method.

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Large-scale topology optimization incorporating local-in-time adjoint-based method for unsteady thermal-fluid problem

Cited by 37 publications

References 18 publications

A Review of Topology Optimisation for Fluid-Based Problems

A Review of Topology Optimisation for Fluid-Based Problems

Computational design of flow fields for vanadium redox flow batteries via topology optimization

Topology optimization of convective heat transfer by the lattice Boltzmann method

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