Inverse analysis of a loaded heat conduction equation

This work considers an inverse problem for a heat conduction equation that includes fractional loaded terms and coefficients varying with spatial coordinates. By reformulating the original equation into a system of equivalent loaded integro-differential equations, we establish sufficient conditions ensuring the existence and uniqueness of the solution. The study focuses on determining the multidimensional kernel associated with the fractional heat conduction operator. The approach is based on the contraction mapping principle and the use of Riemann-Liouville fractional integrals, providing a mathematical framework applicable to diffusion processes with spatial heterogeneity and memory effects.

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Publication Details

Journal
Nanosystems Physics Chemistry Mathematics
Published
2026-01-06
DOI
https://doi.org/10.17586/2220-8054-2025-16-6-727-736
Primary Topic
Fractional Differential Equations Solutions
Type
article
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article

Inverse analysis of a loaded heat conduction equation

Umida Baltaeva, Fabien Hubert, P. Agarwal, B. Khasanov et al.
Nanosystems Physics Chemistry Mathematics
Fractional Differential Equations Solutions
article

Inverse analysis of a loaded heat conduction equation

Umida Baltaeva, Fabien Hubert, P. Agarwal, B. Khasanov, H. Hayitbayev
article en

Abstract

This work considers an inverse problem for a heat conduction equation that includes fractional loaded terms and coefficients varying with spatial coordinates. By reformulating the original equation into a system of equivalent loaded integro-differential equations, we establish sufficient conditions ensuring the existence and uniqueness of the solution. The study focuses on determining the multidimensional kernel associated with the fractional heat conduction operator. The approach is based on the contraction mapping principle and the use of Riemann-Liouville fractional integrals, providing a mathematical framework applicable to diffusion processes with spatial heterogeneity and memory effects.

Nanosystems Physics Chemistry MathematicsVol. 16(6)
Urgench State University (UZ), Aix-Marseille Université (FR), Khan Academy (US), Hodges University (US), Anand International College of Engineering
Openalex Percentile: Top 83%
Fractional Differential Equations Solutions
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