Publication2026
Artificial intelligence-based prediction of heat transfer in the Ellis hybrid nanofluid flow over a stretching cylinder
The record
- Type
- Publication
- Date
- 2 July 2026
- Level
- National
- Journal
- Aip Conference Proceedings
- Volume
- 3289
- Issue
- 1
- Published
- 2 July 2026
- DOI
- 10.1063/5.0328583
- Scopus ID
- 105044959374
- ISSN
- 0094243X
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Machine learning model for predicting heat transfer rate of Ellis hybrid nanofluid flow demonstrates AI-based thermal engineering computational methodology.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
AI-based thermal physics research demonstrates digital technology advancement in computational engineering.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Artificial intelligence-based prediction of heat transfer in the Ellis hybrid nanofluid flow over a stretching cylinder”. Kortex.