A numerical study of space‐fractional three‐phase‐lag bioheat transfer model during thermal therapy

Heat Transfer ◽  
2021 ◽  
Author(s):  
Tejaswini Kumari ◽  
S. K. Singh
Keyword(s):  
Numerical Study ◽  
Thermal Therapy ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Phase Lag ◽  
Three Phase

Numerical simulation of dual-phase-lag bioheat transfer model during thermal therapy

2016 ◽  
Vol 281 ◽  
pp. 82-91 ◽  
Author(s):  
P. Kumar ◽  
Dinesh Kumar ◽  
K.N. Rai
Keyword(s):  
Numerical Simulation ◽  
Thermal Therapy ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Phase Lag ◽  
Dual Phase

Thermal Therapy Protocols for Benign Prostatic Hyperplasia

2007 ◽  
Author(s):  
Daniel Chinn ◽  
Elvis Nditafon ◽  
Alvin Yew ◽  
Chandrasekhar Thamire
Keyword(s):  
Benign Prostatic Hyperplasia ◽  
Thermal Damage ◽  
Prostatic Hyperplasia ◽  
Operating Conditions ◽  
Thermal Therapy ◽  
Bioheat Transfer ◽  
Surrounding Tissue ◽  
Accurate Estimation ◽  
Transfer Model ◽  
Porous Media Model

Thermal therapy for treatment of benign prostatic hyperplasia (BPH) is becoming increasingly popular due to the minimally invasive nature of the treatment. Successful management of such therapy requires accurate estimation of thermal dosage. The purpose of this study is to provide correlations for the thermal damage caused by ultrasound, microwave, and infrared devices under a range of operating conditions. A boundary-fitting finite difference method is used to examine the heat transfer in the prostate gland and surrounding tissue. The Pennes bioheat transfer model and a porous media model were utilized to calculate temperature histories. Necrosis zones were determined using published necrosis data for prostatic tissue and cells. Thermal damage correlations for the three different hyperthermia sources along with sample temperature contours and necrosis zones are presented. Results indicate that the applicator power level and heating time are the most important parameters in achieving the desired necrosis zones, while coolant parameters strongly affect the temperatures of the sensitive urethra and serve as constraints for protocol parameters. Out of the three sources evaluated, ultrasound modality appears to be the most capable of causing necrosis in the target zones, with least damage to the surrounding healthy tissues.

scholarly journals Magnetic resonance temperature imaging validation of a bioheat transfer model for laser‐induced thermal therapy

2011 ◽  
Vol 27 (5) ◽  
pp. 453-464 ◽  
Author(s):  
D. Fuentes ◽  
C. Walker ◽  
A. Elliott ◽  
A. Shetty ◽  
J.D. Hazle ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Thermal Therapy ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Temperature Imaging ◽  
Magnetic Resonance Temperature Imaging

Relationship Between the Nonlocal Effect and Lagging Behavior in Bioheat Transfer

2021 ◽  
Author(s):  
Xiaoya Li ◽  
Yan Li ◽  
Pengfei Luo ◽  
Xiao Geng Tian
Keyword(s):  
Heat Transfer ◽  
Heat Conduction ◽  
Order Effect ◽  
Heat Transfer Process ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Phase Lag ◽  
Medical Systems ◽  
Conduction Model ◽  
Transfer Equations

Abstract Lots of generalized heat conduction models have been developed in recent decades, such as local thermal non-equilibrium model, phase lagging model and nonlocal heat conduction model. But no attempt was made to prove which model is better (or worse) than others, or whether there is a certain relationship between these different models. With this inspiration, we establish the nonlocal bioheat transfer equations with lagging time, and the two and three-temperature bioheat transfer equations with considering all the carries' heat conduction effect are also constructed. Comparing the two (or three)-temperature equation model with the nonlocal bioheat transfer models with lagging time, one may obtain: the lagging time tt of temperature gradient and the nonlocal characteristic length ?q in the space derivative items of heat flux have the same effect on heat transfer; when the heat transport occur among N energy carriers with considering the conduction effects of all carries, the heat transfer process are depend on the high-order effect of tqN-1, ttN-1 and ?t(2N-1) in nonlocal dual phase lag bioheat transfer model. This phenomenon is very important for biological and medical systems where numerous carriers may exist on the cellular level.

scholarly journals A Fibonacci Wavelet Method for Solving Dual-Phase-Lag Heat Transfer Model in Multi-Layer Skin Tissue during Hyperthermia Treatment

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2254
Author(s):  
Hari Mohan Srivastava ◽  
Mohd. Irfan ◽  
Firdous A. Shah
Keyword(s):  
Time Lag ◽  
Blood Perfusion ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Operational Matrices ◽  
Phase Lag ◽  
Dual Phase ◽  
Algebraic Equations ◽  
Hyperthermia Treatment ◽  
Wavelet Collocation Method

In this article, a novel wavelet collocation method based on Fibonacci wavelets is proposed to solve the dual-phase-lag (DPL) bioheat transfer model in multilayer skin tissues during hyperthermia treatment. Firstly, the Fibonacci polynomials and the corresponding wavelets along with their fundamental properties are briefly studied. Secondly, the operational matrices of integration for the Fibonacci wavelets are built by following the celebrated approach of Chen and Haiso. Thirdly, the proposed method is utilized to reduce the underlying DPL model into a system of algebraic equations, which has been solved using the Newton iteration method. Towards the culmination, the effect of different parameters including the tissue-wall temperature, time-lag due to heat flux, time-lag due to temperature gradient, blood perfusion, metabolic heat generation, heat loss due to diffusion of water, and boundary conditions of various kinds on multilayer skin tissues during hyperthermia treatment are briefly presented and all the outcomes are portrayed graphically.

scholarly journals Experimental and numerical study of calcium treatment of steel

2019 ◽  
Vol 116 (5) ◽  
pp. 514 ◽  
Author(s):  
Harsh Priyadarshi ◽  
Benjamin Boissiere ◽  
Pascal Gardin ◽  
Jean Lehmann ◽  
Luisa Silva
Keyword(s):  
Mass Transfer ◽  
Sherwood Number ◽  
Liquid Steel ◽  
Calcium Release ◽  
Numerical Study ◽  
Mass Transfer Rate ◽  
Bench Mark ◽  
Transfer Model ◽  
Calcium Treatment ◽  
Three Phase

This paper presents the laboratory scale experiments of calcium release in liquid steel and its modeling to better understand the mass transfer mechanism occurring during calcium treatment of steel. The calcium injections are performed at the liquid steel temperature below and above the boiling point of calcium (1484 °C). The corresponding yields (calcium recovery) are compared. The objective is to confront the experimental results with the results of the numerical model developed. Rise of calcium droplet in liquid steel is a three-phase problem (calcium droplet/liquid steel/air at the top) therefore an in-house scientific computational platform based on finite element methods is adapted to allow the modeling of such three-phase flows, which is validated using classical bench mark issued from literature. Mass transfer model is first validated by comparison with the analytical solution obtained for a motionless calcium droplet dissolving in stable liquid steel. This case study highlighted the importance and sensitivity on the prediction of concentration profile near the interface with numerical parameters, such as the mesh size. The case of mass transfer for a rising liquid droplet in a liquid matrix is also simulated. The accordance between the calculated Sherwood number and the Sherwood number found in the literature demonstrates the ability of the model to predict the mass transfer rate occurring at the interface.

Evaluation of heat conduction in a laser irradiated tooth with the three-phase-lag bio-heat transfer model

2018 ◽  
Vol 7 ◽  
pp. 203-212 ◽  
Author(s):  
S. Falahatkar ◽  
A. Nouri-Borujerdi ◽  
A. Mohammadzadeh ◽  
M. Najafi
Keyword(s):  
Heat Transfer ◽  
Heat Conduction ◽  
Heat Transfer Model ◽  
Transfer Model ◽  
Phase Lag ◽  
Three Phase

A study of fractional order dual-phase-lag bioheat transfer model

2020 ◽  
Vol 93 ◽  
pp. 102661
Author(s):  
Mahesh kumar ◽  
K.N. Rai ◽  
Rajeev
Keyword(s):  
Fractional Order ◽  
Bioheat Transfer ◽  
Transfer Model ◽  
Phase Lag ◽  
Dual Phase
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