At STARlab, we conduct cutting-edge research at the intersection of fluid mechanics, heat transfer, and space technology, with a dedicated focus on satellite design and manufacturing, as well as planetary science and exploration. Our work spans atmospheric fluid mechanics, energy system design and optimization for satellite platforms and space machines, and the dynamics of air pollution and dust (discrete phase) transport in planetary atmospheres. We leverage machine learning, deep learning, and surrogate modeling techniques to advance both geophysical flow analysis and planetary studies, including the characterization of planetary environments and the thermal and fluid-dynamic challenges of satellite systems. Our research infrastructure is built upon a high-performance, cloud-based computing platform, enabling high-fidelity simulations and data-driven insights. The lab's activities are organized into two principal areas: the development of in-house CFD and predictive model computer codes tailored for satellite and planetary applications, and the detailed simulation of complex problems using commercial CFD software, all with the goal of supporting the design, manufacturing, and operation of next-generation satellites and deepening our understanding of planetary atmospheres and surfaces.
At STARLab
