ANN-Powered Automatic Calculation for Fire Sprinkler Head Needed for Random Car Parking Basement Area | 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 Article ANN-Powered Automatic Calculation for Fire Sprinkler Head Needed for Random Car Parking Basement Area Aditya Chattopadhyay, Pavan Kumar Yadav, Abhishek Maurya, Prateek Priye, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7761209/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract The increasing complexity of fire safety in basement car parking structures, compounded by high fire loads, limited ventilation, and vehicle fires, challenges the adequacy of conventional sprinkler design methods prescribed by standards such as NFPA 13, IS 15105, NBC, and OISD. Basement areas in modern buildings, especially those used for car parking, present unique challenges for fire safety due to their enclosed nature, limited ventilation, and high fire load. The accumulation of vehicles, fuel, and other combustible materials increases the risk of rapid fire spread and smoke retention, making early detection and efficient suppression critical. Automatic sprinkler systems play a vital role in mitigating these risks by providing rapid and uniform water distribution to control or extinguish fires before they escalate. The proposed ANN framework simplifies calculations, eliminates the need for iterative hydraulic methods such as Hazen–Williams, and provides faster, more representative results aligned with real-world fire dynamics. Comparative analysis demonstrates that ANN-based modeling enhances performance by offering dynamic adaptability, precision in design, and resource efficiency, while reducing both over- and under-design risks inherent in traditional methods. The findings highlight ANN-powered sprinkler design as a transformative approach, complementing prescriptive codes and paving the way toward performance-based, adaptive, and smarter fire protection systems for modern urban basement car parking facilities. Physical sciences/Energy science and technology Physical sciences/Engineering Artificial Neural Network (ANN) Sprinkler Design Fire Dynamic Simulation Artificial Intelligence Basement Fire Protection Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 23 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviews received at journal 03 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 03 Dec, 2025 Editor assigned by journal 17 Nov, 2025 Editor invited by journal 04 Nov, 2025 Submission checks completed at journal 14 Oct, 2025 First submitted to journal 14 Oct, 2025 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. 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