Towards a Uncertainty Analysis in Thermal Protection using Phase-change Micro/Nano Particles during Hyperthermia

Abstract

In thermal protection of healthy tissues during hyperthermia with the phase-change micro/nanomaterials, the impossibility of performing a similar experiment with the theo retical parameters is inevitable because of different errors such as modeling, measuring, particle deposition area, etc. These errors may affect the practical thermal protection from damaging the healthy tissue or not destroying the tumor tissue. T o perform a numerical procedure, the electrical potential is obtained solving the Laplace equation and the Pennes Biothermal equation is used to find the temperature distribution in the tissue using the finite difference method. T he Pennes equation is transiently resolved by considering intracellular conductance, blood perfusion, and metabolic heating. Consequently, the deviation and the uncertainty of each parameters in the thermal protection including the concentration of the phase change material, the radius of microcapsules, the latent heat, the melting point, the temperature range of phase change of micro/nanoparticles, and the concentration and the radius of the superparamagnetic materials are investigated. According to the results of the uncertainty analysis, the radius of the superparamagnetic materials is the most important parameter so that a 20% deviation from the numerical value changes the temperature of the tissue up to 4 °C.

Extreme Learning Machine based Pattern Classifiers for Symbolic Interval Data

“…If 𝑎 𝐿 = 𝑎 𝑢 then interval is called to be degenerated, thin or even point interval. Let interval number 𝐴 = [𝑎 𝐿 , 𝑎 𝑈 ]𝑎𝑛𝑑 𝐵 = [𝑏 𝐿 , 𝑏 𝑈 ] ⊂ 𝑅. Intervals are produced for each arithmetic operation in Equations ( 1)- (6).…”

“…In real-life situations, there is imprecise and incompleteness in the feature values [1][2][3][4][5][6]. It is suitable *Corresponding Author Institutional Email: nasibeh.emami@kub.ac.ir (N. Emami) to apply interval feature value for data [7][8][9][10][11].…”

The application of analytical methods in the investigation effects of Magnetic parameter and Brownian motion on the fluid flow between two equal plates

“…mixed convection heat transfer from Al2O3-water nanofluid in W-shaped, copper tube cause the rate of heat transfer coefficient improved with Reynolds number for average wall temperatures of 50 and 60ºC. Magneto hydrodynamic nanofluid flow between two parallel analyzed and results showed concentration of nanofluid diminishes when Brownian movement increments whereas it increases with expands of thermophoretic parameter [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. Gupta et al [21] examined magneto convection in a nanofluid.…”