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Local multi-fidelity surrogates for data-efficient parametric studies of combustion problems

An Elsevier journal article published 2026-01-01 about local multi-fidelity surrogate methods intended for data-efficient parametric analysis in combustion research. The supplied excerpt includes only publisher and content-type metadata and provides no study results or details.

Categories: science-and-space, technology

Generated scores

Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.

Confidence
6/10
Geographic reach
1/10
Global importance
2/10
Impact magnitude
2/10
Positivity
5/10
Urgency
1/10

Why it matters

The paper presents methodological research that is relevant to researchers performing parametric studies in combustion, as indicated by the title.

Sources

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