Large-scale three-dimensional (3D) topology optimization (TO) has been a larger trend for the previous decade. Unlike small-scale 2D simple cases, high-resolution 3D cases feature a much higher computational cost, usually requiring access to large cluster environments, which may not always be available to the general users. Motivated by this observation, we constructed a topology optimization of 3D multiphysics systems. The goal is to allow researchers to solve large-scale 3D multiphysics TO problems for the design of high-performance thermal fluid devices. The key idea behind this is to use two different meshes in this workflow. More specifically, a fine “design mesh” is used for updating design variables and it can capture small design features. A dynamically adapted sparse mesh is used for physics computing and it helps to save huge amounts of computational cost. The mesh adaptation can be performed in a distributed fashion. A finite element interpolator enables parallel interpolation between these two meshes. Furthermore, this fully distributed framework includes scalable domain decomposition, matrix assembly, and linear solver that very few general-purpose libraries offer. To demonstrate the effectiveness of the proposed framework, we present several 2D and 3D design benchmarks including a mean compliance problem, power dissipation problem, fluid-structure interaction (FSI) problem, natural/forced-convection problem, lift-drag problem, feature-rich designs, transient thermal cloaking design. These can be implemented in FreeFEM language interfaced with PETSc and ParMmg library.