A Residual Power Series Framework in Fractional Convection–Diffusion Model with Convergence Analysis and Applications

This work investigates a novel residual power series technique (RPST) to analyze time-fractional convection–diffusion equations (TFC-DEqs) that model transport processes with memory and anomalous diffusion effects. The approach is appropriate for both linear and nonlinear cases because it avoids linearization, discretizations, and other simplifying assumptions. The reliability of the method is demonstrated by the results, which show strong agreement with exact solutions and rapid convergence as the fractional order approaches one. The error analysis also verifies that such results can be obtained with high accuracy by considering only a few terms, which demonstrates the efficiency of the method. A significant outcome of this research is the development of a reliable and efficient analytical framework that can accommodate complex transport phenomena without resorting to assumptions. The results are significant as they offer insights and show promise for potential applications in engineering and applied science, particularly for nonlocal and memory-dependent systems.

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Publication Details

Journal
Fractal and Fractional
Published
2026-09-20
DOI
https://doi.org/10.3390/fractalfract10090656
Primary Topic
Fractional Differential Equations Solutions
Type
article
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0.00
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article

A Residual Power Series Framework in Fractional Convection–Diffusion Model with Convergence Analysis and Applications

Ilhem Kadri, Sajad Iqbal, Nidal E. Taha, Brij Mohan et al.
Fractal and Fractional
Fractional Differential Equations Solutions
article

A Residual Power Series Framework in Fractional Convection–Diffusion Model with Convergence Analysis and Applications

Ilhem Kadri, Sajad Iqbal, Nidal E. Taha, Brij Mohan, Manal Y. A. Juma
article en

Abstract

This work investigates a novel residual power series technique (RPST) to analyze time-fractional convection–diffusion equations (TFC-DEqs) that model transport processes with memory and anomalous diffusion effects. The approach is appropriate for both linear and nonlinear cases because it avoids linearization, discretizations, and other simplifying assumptions. The reliability of the method is demonstrated by the results, which show strong agreement with exact solutions and rapid convergence as the fractional order approaches one. The error analysis also verifies that such results can be obtained with high accuracy by considering only a few terms, which demonstrates the efficiency of the method. A significant outcome of this research is the development of a reliable and efficient analytical framework that can accommodate complex transport phenomena without resorting to assumptions. The results are significant as they offer insights and show promise for potential applications in engineering and applied science, particularly for nonlocal and memory-dependent systems.

Fractal and FractionalVol. 10(9)
University of Delhi (IN), Université Oran 1 Ahmed Ben Bella (DZ), Qassim University (SA), Yangzhou University (CN)
Openalex Percentile: Top 12%
Fractional Differential Equations Solutions
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A Residual Power Series Framework in Fractional Convection–Diffusion Model with Convergence Analysis and Applications — Ilhem Kadri, Sajad Iqbal, et al. · Fractal and Fractional (2026) | TGRS Research Map | TGRS