.png){kind=icon}
.png){kind=icon}
Return
Optimizing Startshot Lightsail Design: A Generative Network-Based Approach
.png){kind=icon}
OA
AI
DOI：10.1021/acsphotonics.1c01352.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The Starshot lightsail project aims to build an ultralight spacecraft (nanocraft) that can reach Proxima Centauri b in approximately 20 years, requiring propulsion with a relativistic velocity of similar to 60 000 km/s. The spacecraft's acceleration approach currently under investigation is based on applying the radiation pressure from a high-power laser array located on Earth to the spacecraft lightsail. However, the practical realization of such a spacecraft imposes extreme requirements on the lightsail's optical, mechanical, thermal properties. Within this work, we apply adjoint topology optimization and a variational autoencoder-assisted inverse design algorithm to develop and optimize a silicon-based lightsail design. We demonstrate that the developed framework can provide optimized optical and opto-kinematic properties of the lightsail. Furthermore, the framework opens up the pathways to realizing a multi-objective optimization of the entire lightsail propulsion system, leveraging the previously demonstrated concept of physics-driven compressed space engineering.
Keywords:
Starshot lightsail
inverse design
topology optimization
machine learning
