Quantitative mapping of computational creep modelling: a review

Abstract

The long-term reliability of structural components operating under high-temperature and stress conditions is critically influenced by creep deformation and rupture. To address this, a wide array of computational creep life assessment models has emerged over the past decade, incorporating empirical, phenomenological, and artificial intelligence (AI)-assisted approaches. This study presents a quantitative bibliometric analysis of global research output from 2012 to 2025, with a focus on the development, performance, and adoption of computational creep models. Using data from Scopus, ScienceDirect, and Google Scholar, and analytical tools such as VOS viewer, this work maps publication trends, influential authors, institutional affiliations, and research clusters. The analysis categorizes key modeling approaches, ranging from classical constitutive laws to advanced continuum damage mechanics and hybrid AI-physics models, while highlighting their industrial relevance in sectors such as power generation, aerospace, and petrochemicals. Furthermore, it identifies underexplored areas, regional disparities, and evolving research frontiers. This study offers critical insights into the trajectory of creep modeling research and provides guidance for future development of more robust, predictive, and computationally efficient creep assessment frameworks.