Scholarlink

<p>When applied to a non-Newtonian fluid, the analysis of the field of fluid mechanics using fractional calculus has revolutionized the modelling of complex systems whose behaviour is memory dependent. This study presents a bibliometric analysis of more than 725 published articles indexed in the Scopus database between 2015 and March 2026. Using VoS viewer and R-Studio, the trends in publications, prolific authors, and key word clusters are examined. It is found that the results are dominated by the magnetohydrodynamic flows and non-Newtonian fluids with fractional derivatives. The structural network is dominated by three major thematic clusters: classical singular operators (60% utilization density), MHD/thermal transport parameters, and emerging data-driven physics-informed optimization schemes. The total network corpus accumulated 12,643 citations with an average 17 citations per paper and an overall dataset H-index of 55. Thematic evaluation reveals that while core clusters (MHD, Darcy flows) are highly saturated, significant gaps persist regarding empirical verification. Nevertheless, the critical research gap, as identified in the analysis, are the lack of experimental validation and the under-use of machine learning in estimating the parameters. The paper can guide researchers to make the transition between the proven solutions of analysis to the new frontiers of the variable-order modelling and AI-based fluid mechanics. Furthermore, this study highlights the need for interdisciplinary collaboration between experimentalists and computational researchers to enhance model reliability and practical applicability. It also provides a structured roadmap for integrating data-driven approaches with fractional frameworks to achieve more accurate and predictive fluid flow models.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A Bibliometric Assessment and Structural Analysis of Fractional Calculus Applications in Non-Newtonian Fluid Dynamics: A Bibliometric Mapping and Gap Analysis (2015- March 2026)

  • 期刊论文

  • 发表日期：

    2026年7月6日

查看全文
  • Nadeem Ahmad Sheikh,
  • Zulkhibri Ismail

摘要

When applied to a non-Newtonian fluid, the analysis of the field of fluid mechanics using fractional calculus has revolutionized the modelling of complex systems whose behaviour is memory dependent. This study presents a bibliometric analysis of more than 725 published articles indexed in the Scopus database between 2015 and March 2026. Using VoS viewer and R-Studio, the trends in publications, prolific authors, and key word clusters are examined. It is found that the results are dominated by the magnetohydrodynamic flows and non-Newtonian fluids with fractional derivatives. The structural network is dominated by three major thematic clusters: classical singular operators (60% utilization density), MHD/thermal transport parameters, and emerging data-driven physics-informed optimization schemes. The total network corpus accumulated 12,643 citations with an average 17 citations per paper and an overall dataset H-index of 55. Thematic evaluation reveals that while core clusters (MHD, Darcy flows) are highly saturated, significant gaps persist regarding empirical verification. Nevertheless, the critical research gap, as identified in the analysis, are the lack of experimental validation and the under-use of machine learning in estimating the parameters. The paper can guide researchers to make the transition between the proven solutions of analysis to the new frontiers of the variable-order modelling and AI-based fluid mechanics. Furthermore, this study highlights the need for interdisciplinary collaboration between experimentalists and computational researchers to enhance model reliability and practical applicability. It also provides a structured roadmap for integrating data-driven approaches with fractional frameworks to achieve more accurate and predictive fluid flow models.