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January 14, 2026Computation2 citationsOpen Access

Multifidelity Topology Design for Thermal–Fluid Devices via SEMDOT Algorithm

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YSYao SunYFYun-Fei FuSXShuzhi Xu

Key Points

  • The aim is to develop a multifidelity topology design framework for efficient thermal-fluid device design.
  • Used a low-fidelity Darcy–convection model for topology optimization.
  • Optimized geometric smoothness with the SEMDOT algorithm while maintaining CAD-ready boundaries.
  • Evaluated designs through high-fidelity Navier–Stokes–convection simulations in COMSOL 6.3.
  • SEMDOT designs reduced peak temperature from approximately 337 K to 323 K.
  • Pressure drop decreased from about 18.7 Pa to 12.6 Pa compared to straight-channel layouts.
  • Achieved a normalized hypervolume of 1.000 versus 0.923 with conventional methods.

Abstract

Designing thermal–fluid devices that reduce peak temperature while limiting pressure loss is challenging because high-fidelity (HF) Navier–Stokes–convection simulations make direct HF-driven topology optimization computationally expensive. This study presents a two-dimensional, steady, laminar multifidelity topology design framework for thermal–fluid devices operating in a low-to-moderate Reynolds number regime. A computationally efficient low-fidelity (LF) Darcy–convection model is used for topology optimization, where SEMDOT decouples geometric smoothness from the analysis field to produce CAD-ready boundaries. The LF optimization minimizes a P-norm aggregated temperature subject to a prescribed volume fraction constraint; the inlet–outlet pressure difference and the P-norm parameter are varied to generate a diverse candidate set. All candidates are then evaluated using a steady incompressible HF Navier–Stokes–convection model in COMSOL 6.3 under a consistent operating condition (fixed flow; pressure drop reported as an output). In representative single- and multi-channel case studies, SEMDOT designs reduce the HF peak temperature (e.g., ~337 K to ~323 K) while also reducing the pressure drop (e.g., ~18.7 Pa to ~12.6 Pa) relative to conventional straight-channel layouts under the same operating point. Compared with a conventional RAMP-based pipeline under the tested settings, the proposed approach yields a more favorable Pareto distribution (normalized hypervolume 1.000 vs. 0.923).

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Cite This Study

Sun et al. (2026) studied this question.

synapsesocial.com/papers/6966f33213bf7a6f02c0107ehttps://doi.org/10.3390/computation14010019
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