Company to Utilize Cutting-Edge Physics-Informed Neural Networks, Predicting Locations of Orbital Debris

Collaboration with NVIDIA to Heighten Operational Speed and Efficiency to Ensure Safety and Operational Integrity of Space Assets

Sierra Space, a leading commercial space company that is Building a Platform in Space to Benefit Life on Earth®, announced today a major advancement in space domain awareness. Leveraging the power of physics-informed neural networks (PINNs) and a collaboration with NVIDIA, Sierra Space is now able to predict the future locations of orbital debris.

As the volume of orbital debris continues to grow, the need for precise and reliable prediction methods has never been more critical to ensure safety and operational integrity of our space assets. Traditional models often fall short in accounting for the complex dynamics of space environments. However, by integrating the principles of physics directly into neural network architectures, Sierra Space has developed a solution that not only enhances prediction accuracy but also significantly reduces computational overhead.

“At Sierra Space, we are committed to pioneering innovative solutions that ensure the safety and operational integrity of our space assets. By leveraging physics-informed neural networks and collaborating with NVIDIA, we are setting a new standard in space domain awareness,” said Sierra Space CEO Tom Vice. “This advancement not only enhances our ability to predict the future locations of orbital objects with unprecedented accuracy but also significantly improves the computational efficiency of our models. Together, we are making space safer for all.”

Innovative Use of Physics-Informed Neural Networks

PINNs represent a revolutionary approach to modeling and predicting the behavior of orbital debris. By embedding physical laws into the neural network’s structure, these models can simulate the intricate interactions and forces acting on debris in orbit. This allows for more accurate predictions of future locations and potential intersections with operational spacecraft.

Sierra Space PINNs are trained to understand and predict the trajectories of debris by incorporating data from various sources, including satellite observations and historical tracking information. This data-driven approach, combined with the inherent understanding of physical laws, enables real-time predictions and alerts, ensuring that operational spacecraft can take timely and effective evasive actions.

Collaborating with NVIDIA: Powering Advanced Computation

Sierra Space’s innovations in space domain awareness initiatives is enabled by a collaboration with NVIDIA. Utilizing NVIDIA AI and accelerated computing for both training and inference, Sierra Space models can achieve heightened computational efficiency and speed. NVIDIA accelerated computing is specifically designed to handle the intensive computational demands of deep learning models, making them an ideal choice for Sierra Space’s PINN-based solutions.

NVIDIA’s GPUs enable the processing of vast amounts of data simultaneously, significantly reducing the time required for model training and inference. This capability is crucial for real-time applications where timely predictions can make the difference between a safe maneuver and a potential collision.

“At Sierra Space, we are constantly pushing the boundaries of what is possible in space. By leveraging the power of NVIDIA accelerated computing and deep learning, we are not only enhancing the accuracy of our predictions but also ensuring the safety and operational integrity of our space assets,” said Dr. Joe Kopacz, Sierra Space’s Vice President of Software Engineering & AI Strategy.

“Our collaboration with NVIDIA has been instrumental in achieving the computational efficiency required for real-time applications. This advancement marks a significant milestone in our mission to protect the space environment and ensure sustainable operations for the future.”

Source: BUSINESS WIRE