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Determining Thermophysical Parameters of Cryopreserved Articular Cartilage Using Evolutionary Algorithms and Experimental Data. | LitMetric

Determining Thermophysical Parameters of Cryopreserved Articular Cartilage Using Evolutionary Algorithms and Experimental Data.

Materials (Basel)

Department of Computational Mechanics and Engineering, Silesian University of Technology, Konarskiego 18A, 44-100 Gliwice, Poland.

Published: November 2024

AI Article Synopsis

  • Cryopreservation is a method used to freeze and store biological cells and tissues, like stem cells and articular cartilage, to maintain their essential functions when thawed.
  • This process is particularly important in medicine for repairing damaged joints, as it allows preserved cartilage to be used for reconstruction.
  • The article discusses a study using numerical methods to analyze heat and mass transfer in cryopreserved cartilage, revealing a small relative error in thermophysical parameters and proposing modified values for better accuracy.

Article Abstract

Cryopreservation is the process of freezing and storing biological cells and tissues with the purpose of preserving their essential physiological properties after re-warming. The process is applied primarily in medicine in the cryopreservation of cells and tissues, for example stem cells, or articular cartilage. The cryopreservation of articular cartilage has a crucial clinical application because that tissue can be used for reconstruction and repair of damaged joints. This article concerns the identification of the thermophysical parameters of cryopreserved articular cartilage. Initially, the direct problem was formulated in which heat and mass transfer were analyzed by applying the finite difference method. After that, at the stage of inverse problem investigations, an evolutionary algorithm coupled with the finite difference method was used. The identification of the thermophysical parameters was carried out on the basis of experimental data on the concentration of the cryoprotectant. In the last part, this article presents the results of numerical analysis for both the direct and inverse problems. Comparing the results for the direct problem, in which the thermophysical parameters are taken from the literature, with the experimental data, we obtained a relative error between 0.06% and 15.83%. After solving the inverse problem, modified values for the thermophysical parameters were proposed.

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Source
http://dx.doi.org/10.3390/ma17235703DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11642555PMC

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