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Thermal damage analysis in tissue caused by electromagnetic radiation using space-time collocation method.

Bhagya Shree Meena1, Sushil Kumar1

  • 1Department of Mathematics, S. V. National Institute of Technology Surat, Gujarat 395007, India.

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|September 27, 2023
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Summary
This summary is machine-generated.

This study models bio-heat transfer using advanced fractional models to understand tissue temperature and thermal damage from electromagnetic radiation. Findings reveal how parameters like blood perfusion and phase lags influence heat effects in tissues.

Keywords:
Chebyshev polynomialsDual-phase-lagElectromagnetic heatingFractional derivativeRBFsSingle-phase-lag

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Area of Science:

  • Biomedical Engineering
  • Computational Physics
  • Thermal Science

Background:

  • External heat sources are increasingly used in medical treatments, necessitating precise control over heat damage.
  • Living tissues exhibit non-homogeneity, requiring consideration of local non-equilibrium effects in thermal behavior analysis.

Purpose of the Study:

  • To investigate thermal damage and temperature distribution in biological tissues subjected to electromagnetic radiation.
  • To analyze the bio-heat transfer using generalized single-phase-lag (SPL) and dual-phase-lag (DPL) models incorporating non-Fourier and non-local effects.

Main Methods:

  • Developed and solved two- and three-dimensional time-space fractional SPL and DPL bio-heat transfer models.
  • Employed a numerical approach combining Gaussian Radial Basis Functions (RBFs) for spatial discretization and shifted Chebyshev polynomials for temporal discretization.
  • Investigated the influence of parameters including blood perfusion rate (Wb), phase lags (τq, τt), and fractional derivative orders (α, β).

Main Results:

  • The numerical solution effectively captures temperature distribution and thermal damage under various physiological and model parameters.
  • Demonstrated the significant impact of blood perfusion, phase lags, and fractional derivative orders on tissue thermal response.
  • Validated the capability of Gaussian RBFs for multidimensional spatial accuracy and Chebyshev polynomials for spectral temporal accuracy.

Conclusions:

  • The generalized fractional SPL and DPL models provide a more comprehensive framework for analyzing bio-heat transfer compared to traditional models.
  • Understanding the interplay of parameters like blood perfusion and phase lags is crucial for optimizing thermal therapies and predicting heat-induced tissue damage.
  • The employed numerical technique offers a robust and accurate method for solving complex bio-heat transfer problems in multidimensional domains.