The thermal performance of heat sinks is enhanced, in the present paper, by applying a material distribution topology optimization approach. We consider solid structures enclosed in three dimensional steady-state conductive differentially heated cavities. The algorithm iteratively updates the geometry of a heat sink, relying on gradient information. The gradient information are computed using adjoint sensitivity methods, combined with high-order accuracy direct numerical simulations. A complete conjugated problem is solved, in which we describe the effect of the solid material on the surrounding flow through the action of a Brinkman friction term in the Navier-Stokes equations, and we map the material distribution function onto the thermal conductivity and heat capacity in the energy conservation equation. Additionally, advanced filtering techniques are applied for enforcing a desired length scale to the solid structure. The success of the method is presented with a thorough physical investigation of the optimal results, which deliver a substantial increase of the heat transfer.

Innovative designs of heat sinks are generated in the present paper through numerical optimization, by applying a material distribution topology optimization approach. The potential of the method is demonstrated in a two-dimensional differentially heated cavity, in which the heat transfer is increased by means of introducing a solid structure that acts as a heat sink. We simulate the heat transfer in the whole system by performing direct numerical simulations of the conjugated problem, i.e. temperature diffusion and convection in the entire domain and momentum conservation in the fluid surrounding the solid. The flow is driven by the buoyancy force, under the Boussinesq approximation, and we describe the presence of solid material as the action of a Brinkman friction force in the Navier–Stokes equations. To obtain a design with a given length scale, we apply regularization techniques by filtering the material distribution. Two different types of filters are applied and compared for obtaining the most realistic solution. Given the large scale of the problem, the optimization is solved with a gradient based method that relies on adjoint sensitivity analysis. The results show the applicability of the method by presenting innovative geometries that are increasing the heat flux. Moreover, the effect of various factors is studied: We investigate the impact of boundary conditions, initial designs, and Rayleigh number. Complex tree-like structures are favored when a horizontal temperature gradient is imposed on the boundary and when we limit the amount of solid volume in the cavity. The choice of the initial design affects the final topology of the generated solid structures, but not their performance for the studied cases. Additionally, when the Rayleigh number increases, the topology of the heat exchanger is able to substantially enhance the convection contribution to the heat transfer. 

Optimization of natural convection-driven flows may provide significant improvements to the performance of cooling devices, but a theoretical investigation of such flows has been rarely done. The present paper illustrates an efficient gradient-based optimization method for analyzing such systems. We consider numerically the natural convection-driven flow in a differentially heated cavity with three Prandtl numbers (Pr= 0.15 - 7 ) at super-critical conditions. All results and implementations were done with the spectral element code Nek5000. The flow is analyzed using linear direct and adjoint computations about a nonlinear base flow, extracting in particular optimal initial conditions using power iteration and the solution of the full adjoint direct eigenproblem. The cost function for both temperature and velocity is based on the kinetic energy and the concept of entransy, which yields a quadratic functional. Results are presented as a function of Prandtl number, time horizons and weights between kinetic energy and entransy. In particular, it is shown that the maximum transient growth is achieved at time horizons on the order of 5 time units for all cases, whereas for larger time horizons the adjoint mode is recovered as optimal initial condition. For smaller time horizons, the influence of the weights leads either to a concentric temperature distribution or to an initial condition pattern that opposes the mean shear and grows according to the Orr mechanism. For specific cases, it could also been shown that the computation of optimal initial conditions leads to a degenerate problem, with a potential loss of symmetry. In these situations, it turns out that any initial condition lying in a specific span of the eigenfunctions will yield exactly the same transient amplification. As a consequence, the power iteration converges very slowly and fails to extract all possible optimal initial conditions. According to the authors’ knowledge, this behavior is illustrated here for the first time.