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A general framework for quantifying uncertainty at scale

Engineering and Technology

A general framework for quantifying uncertainty at scale

I. Farcaş, G. Merlo, et al.

This groundbreaking research by Ionut-Gabriel Farcaş, Gabriele Merlo, and Frank Jenko presents a sensitivity-driven dimension-adaptive sparse grid interpolation strategy, which dramatically enhances uncertainty quantification and sensitivity analysis in large-scale simulations. The method not only achieves highly accurate results with significantly fewer simulations but also showcases an impressive reduction in computational costs, making it a game-changer in fusion research.... show more
Citation Metrics
Citations
16
Influential Citations
0
Reference Count
45
Citation by Year

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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