A Structural Framework for Fire and Explosion Risk in EFRTs: Empirical Validation Using EFA, CFA, and Path Analysis

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Abstract Background: External Floating Roof Tanks (EFRTs) are prone to fire and explosion due to the convergence of human error, technical failure, and weak emergency response. Existing models often use ranking-based methods that fail to reflect systemic interdependencies. This study aimed to develop and validate a structural model that explains the latent constructs underlying EFRT hazards using a theory-informed, data-driven approach. Methods A structured checklist with 71 indicators across 11 domains was developed through expert input and literature review. Data from 285 professionals were analysed using Exploratory Factor Analysis (EFA) to identify key dimensions, followed by Confirmatory Factor Analysis (CFA) and path analysis for model validation. Results EFA extracted 11 factors explaining 72% of the total variance. CFA showed strong fit indices (CFI = 0.915, RMSEA = 0.048). Path analysis confirmed significant causal relationships, including those from operational error to technical failure and fire suppression breakdown. A real-world case study involving 11 EFRTs demonstrated that model-predicted high-risk tanks aligned closely with expert evaluations. Conclusions The final model provides a multidimensional and statistically validated framework for understanding EFRT risks, integrating human, technical, and organizational domains. This model offers practical guidance for safety engineers to identify high-leverage intervention points. It supports the development of predictive safety tools and can be adapted for integration into intelligent fire prevention systems across storage infrastructures.
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A Structural Framework for Fire and Explosion Risk in EFRTs: Empirical Validation Using EFA, CFA, and Path Analysis | 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 A Structural Framework for Fire and Explosion Risk in EFRTs: Empirical Validation Using EFA, CFA, and Path Analysis Parisa Moshashaei, Omid Akbarzadeh, Mohammad Asghari-Jafarabadi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7181189/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background: External Floating Roof Tanks (EFRTs) are prone to fire and explosion due to the convergence of human error, technical failure, and weak emergency response. Existing models often use ranking-based methods that fail to reflect systemic interdependencies. This study aimed to develop and validate a structural model that explains the latent constructs underlying EFRT hazards using a theory-informed, data-driven approach. Methods A structured checklist with 71 indicators across 11 domains was developed through expert input and literature review. Data from 285 professionals were analysed using Exploratory Factor Analysis (EFA) to identify key dimensions, followed by Confirmatory Factor Analysis (CFA) and path analysis for model validation. Results EFA extracted 11 factors explaining 72% of the total variance. CFA showed strong fit indices (CFI = 0.915, RMSEA = 0.048). Path analysis confirmed significant causal relationships, including those from operational error to technical failure and fire suppression breakdown. A real-world case study involving 11 EFRTs demonstrated that model-predicted high-risk tanks aligned closely with expert evaluations. Conclusions The final model provides a multidimensional and statistically validated framework for understanding EFRT risks, integrating human, technical, and organizational domains. This model offers practical guidance for safety engineers to identify high-leverage intervention points. It supports the development of predictive safety tools and can be adapted for integration into intelligent fire prevention systems across storage infrastructures. Physical sciences/Engineering Physical sciences/Mathematics and computing External Floating Roof Tanks (EFRTs) Fire and Explosion Risk Exploratory and Confirmatory Factor Analysis (EFA/CFA) Path Analysis Petroleum Storage Safety. Occupational Safety Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 11 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviews received at journal 25 Aug, 2025 Reviewers agreed at journal 18 Aug, 2025 Reviewers invited by journal 05 Aug, 2025 Editor assigned by journal 04 Aug, 2025 Editor invited by journal 01 Aug, 2025 Submission checks completed at journal 30 Jul, 2025 First submitted to journal 28 Jul, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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