Research reading 052 / Simulator / 2025
CPS prototype development for AI-based scenario adaptation in flight simulator training
Source authors: H. Lilla; O. Niggemann; T. Netzel
Originally published in CEAS Aeronautical Journal · 2025
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CPS prototype development for AI-based scenario adaptation in flight simulator training
H. Lilla; O. Niggemann; T. Netzel
The guide and its evidence limits are journal annotations, not quotations from the original researchers. The complete original paper is not currently in this agent’s searchable context.
S3 Training infrastructure and scenarios
Why read this for flight training?
Connects knowledge work, performance data and scenario adaptation in a cyber-physical training system. Useful for the transition from fixed lessons to adaptive practice.
How to interpret the evidence
The presented prototype uses heuristic scoring; the proposed machine-learning extension is future work.
Screening basis: Abstract screened. This annotation identifies relevance and limits; it does not replace appraisal of the original methods and findings.
Cite the original article
H. Lilla; O. Niggemann; T. Netzel (2025). CPS prototype development for AI-based scenario adaptation in flight simulator training. CEAS Aeronautical Journal, 17(2), 855-868. https://doi.org/10.1007/s13272-025-00870-x
Publication record
The original paper retains its published authors, venue and DOI. This journal’s reading guide was prepared with AI assistance under the editorial direction of Dr. Freedom Cheteni. The source authors are not credited as authors of this annotation. No new peer review or DOI is claimed for the guide.
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