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AI & Foundations

Multiscale Modeling

Phenomena spanning atoms to devices cannot be captured at one resolution; multiscale modeling links models across scales that no single method reaches.

The Scale Problem

Many real systems involve processes across scales so far apart that no single model can resolve them all. Resolving atomic motion while simulating a whole device would demand impossibly many steps and points. Multiscale modeling couples models built for different scales so that fine-scale physics informs coarse-scale behavior without simulating everything everywhere.

Bridging Strategies

Kronos motion — multiscale

The Central Difficulty

The hard part is the coupling: how information passes between scales without introducing artifacts. Averaging fine behavior into a coarse parameter loses information, and choosing what to keep is a modeling judgment with real consequences. A poorly designed scale bridge can corrupt the whole result while looking plausible, so the coupling deserves as much scrutiny as the individual models.

Separation of Scales

Multiscale methods work cleanly when scales are well separated, when fast processes reach a steady state before slow ones change, so each can be treated in its own right. When scales are not separated and interact strongly across the whole range, the problem is far harder, and simple parameter-passing between models can fail badly.

In Fusion Modeling

A fusion device spans electron gyration to whole-machine equilibrium, and material behavior spans atomic damage to component lifetime. Kronos design work uses scale-appropriate models linked by physically justified coupling, and states which effects each scale captures, so that a coarse-scale result rests on defensible fine-scale inputs rather than convenient assumptions.