{"paper_id":"b42a7eed-d4f5-4989-bd59-c0bbce1e2082","body_text":"Experimental investigation and data-driven modeling of nanofluid pool boiling under rotational hypergravity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Experimental investigation and data-driven modeling of nanofluid pool boiling under rotational hypergravity Gen Li, Ao Tian, Yafeng Chen, Xiaojie Zhang, Jianxun Xie, Xiande Fang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8827098/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Apr, 2026 Read the published version in Heat and Mass Transfer → Version 1 posted 16 You are reading this latest preprint version Abstract The coupling effects of rotational hypergravity (1–3.16g) and nanoparticle concentration on the nucleate pool boiling heat transfer of Al 2 O 3 -water nanofluids were experimentally investigated. Contrary to the monotonic deterioration reported in previous literature, this study reveals a distinct enhancement-deterioration non-monotonic trend in the heat transfer coefficient (HTC). The HTC peaks at approximately 1.41g due to buoyancy-assisted bubble detachment but deteriorates sharply at 3.16g. Mechanism analysis elucidates that this degradation is governed by hypergravity-induced sedimentation, where Stokes settling overrides Brownian diffusion, forming a compact thermal resistance layer. Furthermore, the nanoparticle concentration exhibits a complex non-linear impact: while intermediate concentrations cause surface clogging, an optimal concentration of 0.015 wt.% yields maximum enhancement by reconstructing the surface into a three-dimensional (3D) porous structure with strong capillary wicking effects. To address the failure of classical semi-empirical correlations in this coupled regime, machine learning (ML) algorithms were implemented. The XGBoost model demonstrated exceptional fidelity with coefficient of determination (R 2 ) = 0.998, root mean square error (RMSE) = 1.2% and mean absolute error (MAE) = 0.8%, successfully capturing the complex non-linear boundaries of hypergravity and surface fouling. These findings provide robust theoretical insights and predictive tools for aerospace thermal management systems. Nucleate pool boiling heat transfer coefficient nanofluid hypergravity machine learning Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Apr, 2026 Read the published version in Heat and Mass Transfer → Version 1 posted Editorial decision: Revision requested 16 Mar, 2026 Reviews received at journal 16 Mar, 2026 Reviews received at journal 16 Mar, 2026 Reviews received at journal 14 Mar, 2026 Reviews received at journal 12 Mar, 2026 Reviewers agreed at journal 08 Mar, 2026 Reviewers agreed at journal 06 Mar, 2026 Reviewers agreed at journal 06 Mar, 2026 Reviewers agreed at journal 05 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 04 Mar, 2026 Reviewers agreed at journal 03 Mar, 2026 Reviewers invited by journal 03 Mar, 2026 Editor assigned by journal 26 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 09 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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