Design and validation of topology optimized heat exchangers

Saviers, Kimberly R.; Ranjan, Ram; Mahmoudi, Reza

doi:10.2514/6.2019-1465

Cited by 12 publications

(13 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The topology optimization of such systems proves quite challenging, in part due to the modelling and the implementation of a non-mixing constraint between different input channels. It has been an active research issue since the seminal MSc thesis [76], see notably the recent works [80,48,81,79,87,58] and the introduction in [54] for an overview.…”

Section: Introductionmentioning

confidence: 99%

Body-fitted topology optimization of 2D and 3D fluid-to-fluid heat exchangers

Feppon

Allaire

Dapogny

et al. 2021

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

We present a topology optimization approach for the design of fluid-to-fluid heat exchangers which rests on an explicit meshed discretization of the phases at stake, at every iteration of the optimization process. The considered physical situations involve a weak coupling between the Navier-Stokes equations for the velocity and the pressure in the fluid, and the convection-diffusion equation for the temperature field. The proposed framework combines several recent techniques from the field of shape and topology optimization, and notably a level-set based mesh evolution algorithm for tracking shapes and their deformations, an efficient optimization algorithm for constrained shape optimization problems, and a numerical method to handle a wide variety of geometric constraints such as thickness constraints and non-penetration constraints. Our strategy is applied to the optimization of various types of heat exchangers. At first, we consider a simplified 2D cross-flow model where the optimized boundary is the section of the hot fluid phase flowing in the transverse direction, which is naturally composed of multiple holes. A minimum thickness constraint is imposed on the cross-section so as to account for manufacturing and maximum pressure drop constraints. In a second part, we optimize the design of 2D and 3D heat exchangers composed of two types of fluid channels (hot and cold), which are separated by a solid body. A non-mixing constraint between the fluid components containing the hot and cold phases is enforced by prescribing a minimum distance between them. Numerical results are presented on a variety of test cases, demonstrating the efficiency of our approach in generating new, realistic, and unconventional heat exchanger designs.

show abstract

Section: Introductionmentioning

confidence: 99%

Body-fitted topology optimization of 2D and 3D fluid-to-fluid heat exchangers

Feppon

Allaire

Dapogny

et al. 2021

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

show abstract

“…Therefore, the [45] method is shape optimization, rather than topology optimization. [76] obtains three-dimensional heat exchanger designs, however, very few details of the methodology are explained due to proprietary reasons. [54] design a two dimensional unit cell of an air-water heat exchanger.…”

Section: Introductionmentioning

confidence: 99%

Two Dimensional Topology Optimization of Heat Exchangers with the Density and Level-Set Methods

Troya¹,

Tortorelli²,

Beck³

2021

14th WCCM-ECCOMAS Congress

View full text Add to dashboard Cite

We design heat exchangers using two topology optimization approaches: the density, i.e. volume fraction and level set methods. Our goal is to maximize the heat exchange between two fluids in separate channels while constraining the pressure drop across each channel. The heat exchanger is modeled with a coupled thermal-flow formulation. The flow is governed by an isothermal and incompressible Stokes-Brinkman equation and the heat transfer is governed by a convection-diffusion equation with high Peclet number. We solve one set of Stokes-Brinkman equations per fluid. Each Brinkman term in the flow equation serves to model the other phase as a solid, thereby preventing mixing. We first represent the solid and fluid phases using a volume fraction variable and apply a SIMP-like penalization in the Brinkman term to drive the optimization to a discrete design. The cost and constraint function derivatives are automatically calculated with the library pyadjoint and the optimization is performed by the Method of Moving Asymptotes. In a second optimization formulation, we use the level set approach to define the interface that separates the two fluids. Pyadjoint calculates the shape derivatives of the cost and constraint functions and the Hamilton-Jacobi advects the interface, allowing for topological changes. We present results in two dimensions and discuss the advantages and disadvantages of each approach.

show abstract

“…Fairly many works have proposed topology optimization methods for situations where several of the aforementioned physical effects arise: convective heat transfer problems (involving coupled fluid and thermal equations, where the elastic response of the underlying structure is neglected) have been addressed using density methods [73,34,38,109,97,37,36,86,91], or variants of the level-set method [4,29,107]. Systems featuring interactions between a fluid and a solid phase, without taking thermal effects into account, have been studied in slightly fewer works, and in two space dimensions only [108,80,14,57,72,66].…”

Section: Introductionmentioning

confidence: 99%

“…In this work, we resort to preconditioned iterative methods and to distributed computing techniques which allow to solve large-scale finite element problems in parallel at a reduced time-and memory-cost. This type of strategy is classical and has been implemented by many works relying on density methods in the context of the optimization of mechanical structures [2,76,13] or of heat convection systems [91,86,5,23,97]. Interestingly, this trend is also emerging in other design optimization methods, such as evolutionary topology optimization [75] or level-set methods [61].…”

Section: Introductionmentioning

confidence: 99%

Topology optimization of thermal fluid–structure systems using body-fitted meshes and parallel computing

Feppon

Allaire

Dapogny³

et al. 2020

Journal of Computational Physics

View full text Add to dashboard Cite

An efficient framework is described for the shape and topology optimization of realistic threedimensional, weakly-coupled fluid-thermal-mechanical systems. At the theoretical level, the proposed methodology relies on the boundary variation of Hadamard for describing the sensitivity of functions with respect to the domain. From the numerical point of view, three key ingredients are used: (i) a level set based mesh evolution method allowing to describe large deformations of the shape while maintaining an adapted, highquality mesh of the latter at every stage of the optimization process; (ii) an efficient constrained optimization algorithm which is very well adapted to the infinite-dimensional shape optimization context; (iii) efficient preconditioning techniques for the solution of large finite element systems in a reasonable computational time. The performance of our strategy is illustrated with two examples of coupled physics: respectively fluid-structure interaction and convective heat transfer. Before that, we perform three other test cases, involving a single physics (structural, thermal and aerodynamic design), for comparison purposes and for assessing our various tools: in particular, they prove the ability of the mesh evolution technique to capture very thin bodies or shells in 3D.

show abstract

Design and validation of topology optimized heat exchangers

Cited by 12 publications

References 11 publications

Body-fitted topology optimization of 2D and 3D fluid-to-fluid heat exchangers

Body-fitted topology optimization of 2D and 3D fluid-to-fluid heat exchangers

Two Dimensional Topology Optimization of Heat Exchangers with the Density and Level-Set Methods

Topology optimization of thermal fluid–structure systems using body-fitted meshes and parallel computing

Contact Info

Product

Resources

About