The intersection of AI and simulation in the space industry

The capability and reach of artificial intelligence (AI) are continually expanding to meet the needs of increasing complexity of systems in many industries, including the space industry. As a result, engineers are faced with new challenges such as verification and validation as they are tasked with integrating AI into systems. Part of the complexity stems from the recognition that AI models are only as effective as the data they’re trained with – if that data is insufficient, inaccurate, or biased, the model’s calculations will be too.

At a high level, there are three crucial ways AI and simulation are intersecting in space. The first is addressing the challenge of insufficient data, as simulation models can synthesize data that might be difficult or expensive to collect. The second is using AI models as approximations for complex high-fidelity simulations that are computationally expensive, also referred to as reduced-order modeling. The third is the use of AI models in embedded systems for applications such as supervisory logic, signal processing, and embedded vision, where simulation has become a key part of the design process.

Read the article here: www.aerospacemanufacturinganddesign.com/news/the-intersection-ai-and-simulation-in-space-industry/