A Novel Scientific Model for Enhancing Magnetic Confinement Efficiency in Fusion Reactors

A Novel Scientific Model for Enhancing Magnetic Confinement Efficiency in Fusion Reactors | 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 A Novel Scientific Model for Enhancing Magnetic Confinement Efficiency in Fusion Reactors Saleh Ali Saleh Al-Hamed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6975607/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study introduces a novel scientific framework aimed at improving magnetic confinement efficiency in nuclear fusion reactors. By integrating magnetohydrodynamic (MHD) stability theory with adaptive neural network control algorithms, the proposed model offers enhanced real-time plasma confinement under dynamic conditions. Numerical simulations based on modified Grad-Shafranov equations and Lyapunov stability criteria demonstrate a substantial improvement in energy confinement time (τ_E) by approximately 𝜏45.7%, and a reduction in plasma instabilities by nearly 47%, compared to conventional PID-based control models. The model leverages Python-based simulation using open-source fusion modeling tools and presents new possibilities for hybrid AI-assisted fusion systems. While the results are promising, experimental validation in tokamak-scale devices such as ITER or Wendelstein 7-X is essential. This research contributes to the evolving landscape of fusion energy and proposes a path toward robust plasma control through advanced computational techniques. Nuclear Physics Magnetic Confinement Fusion Adaptive Neural Control Plasma Stability Lyapunov Methods Tokamak Stellarator Real-Time Plasma Control Magnetohydrodynamics (MHD) Energy Confinement Time (τ_E) Artificial Intelligence in Fusion Reactors Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6975607","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476372955,"identity":"fc1fbe52-33bb-437d-b060-14fbb0d31b68","order_by":0,"name":"Saleh Ali Saleh Al-Hamed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYFAC5gZmECXP3gAkDSyI0cII0WLYcwCkRYIELQw3EkAkEVrk2w82Pi5gOCzHOPP51Q0/CiQY+Nu7E/BqMTiT2Gw8g+GwMbt0TtnNHqDDJM6c3YBfC0NimzQPw+HExtk5aTd4gFoMJHLxa5Hvf9j+G6ilvuHmmbSbf4jRwnAjsY0ZqCWB4Qb7sdtE2WJw42GzNI9BuuHGnhy22zIGEjwE/SLfn3zwM0+Ftbw8+/FnN9/8sZHjb+8l4DCIXc1AgscAxOQhQjkY1AEx+wNiVY+CUTAKRsEIAwAtS0Z5EAz2eQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0005-1814-5499","institution":"Independent Researcher","correspondingAuthor":true,"prefix":"","firstName":"Saleh","middleName":"Ali Saleh","lastName":"Al-Hamed","suffix":""}],"badges":[],"createdAt":"2025-06-25 14:08:28","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-6975607/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6975607/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":85513783,"identity":"8527d473-ddca-426e-afac-7758fcd22366","added_by":"auto","created_at":"2025-06-26 17:19:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":353308,"visible":true,"origin":"","legend":"","description":"","filename":"ANovelScientif1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6975607/v1_covered_6dc58441-afcb-4351-8b63-3d03f7c9b697.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eA Novel Scientific Model for Enhancing Magnetic Confinement Efficiency in Fusion Reactors\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Magnetic Confinement Fusion, Adaptive Neural Control, Plasma Stability, Lyapunov Methods, Tokamak, Stellarator, Real-Time Plasma Control, Magnetohydrodynamics (MHD), Energy Confinement Time (τ_E), Artificial Intelligence in Fusion Reactors","lastPublishedDoi":"10.21203/rs.3.rs-6975607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6975607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study introduces a novel scientific framework aimed at improving magnetic confinement efficiency in nuclear fusion reactors. 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