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Thermal metamaterials are gaining increasing popularity, especially for heat flux manipulation purposes. However, due to the high anisotropy of the structures resulting from the transformation thermotics or scattering cancellation methods, researchers are resorting to topology optimization as an alternative to find the optimal distribution of constituent bulk materials to realize a specific thermal function. This paper proposes to design a thermal cloak using the level-set-based shape and topology optimization. The thermal cloak design is considered in the context of pure heat conduction. The cloaking effect is achieved by reproducing the reference temperature field through the optimal distribution of two thermally conductive materials. The structural boundary is evolved by solving the Hamilton-Jacobi equation. The feasibility and validity of the proposed method to design thermal meta-devices with cloaking functionality are demonstrated through two numerical examples. The optimized structures have clear boundaries between constituent materials and do not exhibit thermal anisotropy, making it easier for physical realization. The first example deals with a circular cloaking region as a benchmark design. The robustness of the proposed method against various cloaking regions is illustrated by the second example concerning a human-shaped cloaking area. This work can inspire a broader exploration of the thermal meta-device in the heat flux manipulation regime. 

This paper proposes a density-based topology optimization scheme to design a heat sink for the application of a 3D integrated SIC-based 75 kVA Intelligent Power Stage (IPS). The heat sink design considers the heat conduction and convection effects with forced air cooling. The objective function is to minimize the thermal compliance of the whole structure. A volume constraint is imposed to reduce the overall volume of the designed heat sink to make it conformal to the underlying power devices. Some numerical techniques like filtering and projection schemes are employed to render a crisp design. Some 2D benchmarks examples are first provided to demonstrate the effectiveness of the proposed method. Then a 3D heat sink, especially designed for the 3D IPS, is topologically optimized. The classic tree-like structure is reproduced to reinforce the convection effect. Some comparisons with the intuitive baseline designs are made through numerical simulation. The optimized heat sinks are shown to provide a more efficient cooling performance for the 3D integrated power converter assembly. 

In this paper, the authors propose a new dimension reduction method for level-set-based topology optimization of conforming thermal structures on free-form surfaces. Both the Hamilton-Jacobi equation and the Laplace equation, which are the two governing PDEs for boundary evolution and thermal conduction, are transformed from the 3D manifold to the 2D rectangular domain using conformal parameterization. The new method can significantly simplify the computation of topology optimization on a manifold without loss of accuracy. This is achieved due to the fact that the covariant derivatives on the manifold can be represented by the Euclidean gradient operators multiplied by a scalar with the conformal mapping. The original governing equations defined on the 3D manifold can now be properly modified and solved on a 2D domain. The objective function, constraint, and velocity field are also equivalently computed with the FEA on the 2D parameter domain with the properly modified form. In this sense, we are solving a 3D topology optimization problem equivalently on the 2D parameter domain. This reduction in dimension can greatly reduce the computing cost and complexity of the algorithm. The proposed concept is proved through two examples of heat conduction on manifolds. 

Abstract A large amount of energy from power plants, vehicles, oil refining, and steel or glass making process is released to the atmosphere as waste heat. The thermoelectric generator (TEG) provides a way to reutilize this portion of energy by converting temperature differences into electricity using Seebeck phenomenon. Because the figures of merit zT of the thermoelectric materials are temperature-dependent, it is not feasible to achieve high efficiency of the thermoelectric conversion using only one single thermoelectric material in a wide temperature range. To address this challenge, the authors propose a method based on topology optimization to optimize the layouts of functional graded TEGs consisting of multiple materials. The multimaterial TEG is optimized using the solid isotropic material with penalization (SIMP) method. Instead of dummy materials, both the P-type and N-type electric conductors are optimally distributed with two different practical thermoelectric materials. Specifically, Bi2Te3 and Zn4Sb3 are selected for the P-type element while Bi2Te3 and CoSb3 are employed for the N-type element. Two optimization scenarios with relatively regular domains are first considered with one optimizing on both the P-type and N-type elements simultaneously, and the other one only on single P-type element. The maximum conversion efficiency could reach 9.61% and 12.34% respectively in the temperature range from 25 °C to 400 °C. CAD models are reconstructed based on the optimization results for numerical verification. A good agreement between the performance of the CAD model and optimization result is achieved, which demonstrates the effectiveness of the proposed method. 

Over 50% of the energy from power plants, vehicles, oil refining, and steel or glass making process is released to the atmosphere as waste heat. As an attempt to deal with the growing energy crisis, the solid-state thermoelectric generator (TEG), which converts the waste heat into electricity using Seebeck phenomenon, has gained increasing popularity. Since the figures of merit of the thermoelectric materials are temperature dependent, it is not feasible to achieve high efficiency of the thermoelectric conversion using only one single thermoelectric material in a wide temperature range. To address this challenge, this paper proposes a method based on topology optimization to optimize the layouts of functional graded TEGs consisting of multiple materials. The objective of the optimization problem is to maximize the output power and conversion efficiency as well. The proposed method is implemented using the Solid Isotropic Material with Penalization (SIMP) method. The proposed method can make the most of the potential of different thermoelectric materials by distributing each material into its optimal working temperature interval. Instead of dummy materials, both the P and N-type electric conductors are optimally distributed with two different practical thermoelectric materials, namely Bi2Te3 & PbTe for P-type, and Bi2Te3 & CoSb3 for N-type respectively, with the yielding conversion efficiency around 12.5% in the temperature range Tc = 25°C and Th = 400°C. In the 2.5D computational simulation, however, the conversion efficiency shows a significant drop. This could be attributed to the mismatch of the external load and internal TEG resistance as well as the grey region from the topology optimization results as discussed in this paper.