Photothermal therapy for cancer treatment involves complex heat transfer processes. While models have been developed, their ability to provide meaningful results for real cases, making the simulation useful for practical applications, has not been the central focus of previous studies. This work focuses on the validation of a computational model developed within the broader context of research aimed at creating a general framework for simulating photothermal therapy. The validation process involves applying the model to simulate a real treatment and comparing the results to reference values outlined in a treatment protocol. The results align closely with these expected outcomes, increasing model reliability. Additionally, the study provides guidance on the selection of optical and thermophysical properties of human tissues, offering a pathway to more accurate simulations.

Photothermal therapy (PTT) utilizes thermal radiation to heat a targeted tissue for cancer treatment. Nanoparticles can be embedded in tissue regions to enhance radiation absorption, a practice known as plasmonic photothermal therapy (PPTT). Developing models for heat transfer simulation in PTT would be quite useful for supporting experiments and therapies. An important and complex part of such models is radiation scattering. The focus in this research is scattering phase functions of nanoparticles with the evaluation of the widely employed transport approximation (TA). Two TA approaches are considered: TA1 disregards the phase function asymmetry of nanoparticles, common in PTT applications, while TA2 takes it into account. Results obtained for gold nanospheres and nanoshells using the TA were compared with results accurately computed with the Monte Carlo method taking into account detailed Mie phase functions. Evaluation involved direct comparison of heat fluxes and transient temperature distribution. The impact of nanoparticle size variability was also investigated. Results clearly show that within scenarios encountered in real PTT, with nanoparticles ranging from 50 to 100 nm, the transport approximation is quite reliable. For a larger range of scenarios, which can occur in experimental conditions, imaging applications, and due to nanoparticle size variability, TA can still be accurate with the aid of the TA2 approach.

Finned tubes exist in diverse geometric configurations, usually the convective heat transfer coefficient is unknown and approximated as that for a geometry similar to the actual one. This paper presents a numerical investigation about the convective heat transfer in a horizontal finned tube. Ten geometric configurations were considered, which differed on the distance between fins, and two materials were analysed for the fins: aluminium and carbon steel. Eleven different values were considered for the temperature difference between the base of the tube and air. Therefore, a total of one hundred and ten different conditions were studied, for each material. The flow regime was laminar. The analysis showed that approximating the convective heat transfer of the finned tube as that for a tube without fins, for which correlations are available in the literature, can lead to significant errors. The maximum difference verified was for the spacing between fins equal to 2 mm, for which the convective heat transfer coefficient was about seven times lower than that for the tube without fins. For spacings equal to 6 mm and 8 mm, associated to the maximum heat transfer rate, the convective heat transfer coefficient for the tube without fins was about 30% to 50% higher than that for the finned tube. The common assumption of uniform fins surface temperature was also evaluated for the two considered materials the fins were made of. The results showed that for the steel fins the approximation leads to an error of about 10%, while for aluminium it is only about 3%. Results that allow a better understanding of the physical phenomena related to the occurrence of the optimum spacing between fins, which maximize the heat transfer, are also presented and analysed.

Due to economic and environmental reasons, there is an important demand to improve durability and fuel efficiency of jet engines for commercial aviation. Computer simulations are largely employed with the goal of gaining knowledge for design and optimization of the engines. Simulations are increasingly realistic, tanking into account complex coupled phenomena. However, radiation is often either neglected or included using quite simple models for the spectral dependence of the radiative properties. In this paper, the radiative transfer is accurately solved line-by-line for a one-dimensional gas slab with temperature, pressure and H2O, CO2 and CO molar fractions encountered in a jet engine combustor. These gas properties were selected from results obtained by a CFD simulation of a jet engine combustor-turbine, which was accomplished by researchers of NASA John H. Glenn Research Center, considering a realistic geometry and high-fidelity models for combustion, fuel injection and turbulence. The line-by-line solution obtained for such realistic gas serves as benchmark to simpler spectral models which could be further applied in highly computational time consuming coupled simulations of jet engines. In addition, the obtained results allowed to estimate the radiative heat transfer to critical regions of the engine and verify the relative importance of emitting/absorbing species, showing that CO2 has minor importance, while the H2O dominates the radiative transfer. (C) 2019 Elsevier Ltd. All rights reserved.

In the full spectrum k-distribution method, the k-distributions are Planck function weighted. These k-distributions depend on temperature, which varies with location in nonisothermal media. Consequently, in order to apply the method to nonuniform media, k-distributions evaluated at different local temperatures are correlated by a k-distribution evaluated at an arbitrarily chosen reference blackbody temperature. On the other hand, in the original band method, the k-distributions are directly related to spectral locations. Such k-distributions can replace Planck function weighted k-distributions computed at a reference temperature. This approach was employed by Maurente et al. [1] in order to deal with gas mixtures in non-equilibrium media. In this paper the formulation is presented for the equilibrium case. The proposed formulation simplifies the application of the FSK method to nonuniform media, and brings new directions to k-distribution issues. It can be employed with a reference state, but not a reference temperature, with reference state and temperature, as in the traditional FSK, and without any reference state, being in this case the continuous limit of the recently developed Rank Correlated SLW [2]. Results were obtained for test cases considering one-dimensional, nonuniform media, constituted by CO2 and inert gases, and compared to line-by-line solutions.

The multi-spectral energy bundle (MSB) is a method proposed to reduce the computational time of Monte Carlo simulations in media with spectrally dependent properties. In this method the typical energy bundles of the Monte Carlo are treated as multi-spectral by assuming that they are composed of a set of monochromatic sub-bundles. The number of sub-bundles in each bundle affects the computational time in such a way that there exists an optimum number of sub-bundles that leads to the minimum time for the computation. However, due to the stochastic nature of the Monte Carlo, the optimum number of sub-bundles is not easy to be exactly found. This paper proposes a methodology which allows to accurately determine the number of sub-bundles for the minimum computational time, and apply the proposed methodology to 25 cases consisting of a one-dimensional slab of gas composed of H $$_2$$ O and non-emitting/absorbing species, where the FSK was used to consider spectral dependence of properties. The results showed that for the majority of the considered cases, 3 sub-bundles lead to either the minimum or a computational time quite close to the minimum, and always provides reduction of computational time. Thus, 3 sub-bundles is indicated for the analyzed class of problems.

Photothermal therapy (PTT) with combined use of laser radiation and photon absorber nanoparticles is a promising technique to treat cancer. Treatment planning and devising appropriate protocols for cancer photo thermal therapy require the computational simulation of coupled physical phenomena, such as radiation, conduction, and blood perfusion. The P1-approximation is a numerical method to solve radiation heat transfer which features the advantage of being computationally fast and, therefore, desirable for PTT simulations. However, the method is known to become inaccurate under certain conditions. In this study, the P1-approximation and the accurate discrete ordinate method were applied to solve a set of test problems idealized to portray conditions encountered in PTT. The test problems were one-dimensional, and the radiation scattering was assumed as isotropic. Tissues composed by layers with different properties were considered, including cases in which gold nanoparticles were embedded in the tissue to increase photon absorption. For the problems considered here, the P1-approximation and discrete ordinate method results presented quite good agreement for the time-dependent temperature distribution, which is the quantity of interest in PTT.

The Multi-Spectral Energy Bundle (MSB) is a method proposed to reduce the computational time of Monte Carlo simulations in media with spectrally dependent properties. The method has previously been applied for FSK computations. In this paper it is presented the first application of the MSB to line-by-line Monte Carlo computations, and demonstrated that the method can significantly reduce the required computational time.

The Monte Carlo method is a powerful technique for simulating radiation heat transfer processes. The method can easily deal with irregular three-dimensional geometries, anisotropic scattering of radiation and other complexities, which are usually difficult to be tackled with other numerical techniques. On the other hand, Monte Carlo computations are highly time consuming. In addition, accurate radiation heat transfer solutions require that spectral properties be taken into account in a detailed manner, being the line-by-line integration the more accurate but also more computationally expensive technique. Due to these reasons, Monte Carlo computations that accurately consider the spectral properties of radiation are impracticable for several cases of interest in engineering. Therefore reducing the computer time associated to Monte Carlo simulations is highly desirable. This paper presents the Multi-Spectral Energy Bundle method, which reduces the computational time of Monte Carlo simulations in which the spectral properties are accurately taken into account. The method can be applied for line-by-line computations as well as along with spectral models. Here, the proposed method is applied with the accurate full-spectrum k-distribution method, and the obtained results are analyzed. (C) 2015 Elsevier Ltd. All rights reserved.

Approximations for joint cumulative k-distribution for mixtures are efficient for full spectrum k-distribution (FSK) computations. These approximations provide reduction of the database that is necessary to perform FSK computation when compared to the direct approach, which uses cumulative k-distributions computed from the spectrum of the mixture, and also less computational expensive when compared to techniques in which RTE's are required to be solved for each component of the mixture. The aim of the present paper is to extend the approximations for joint cumulative k-distributions for non-LTE media. For doing that, a FSK to non-LTE media formulation well-suited to be applied along with approximations for joint cumulative k-distributions is presented. The application of the proposed methodology is demonstrated by solving the radiation heat transfer in non-LTE high temperature plasmas composed of N, O, N2, NO, N2+ and mixtures of these species. The two more efficient approximations, that is, the superposition and multiplication are employed and analyzed.

Aprocedure has been developed to couple a hypersonic reacting flowmodel, a radiative heat transfermodel, and a surface ablation model to study the surface heat transfer and surface ablation rate of atmospheric reentry vehicles. The two-way loose-coupling algorithm is described for each of the models, as is the solution procedure to achieve convergence. Observations on the challenges of the loose-coupling strategy are given. Representative results are presented for two-dimensional benchmark examples and for three-dimensional flow at an angle of attack past a symmetric capsule based on the Crew Exploration Vehicle reentry vehicle. Effects due to the interaction with radiation and ablation are shown for two quantities of interest: the predicted peak surface heat flux and the ablation rate on the vehicle heat shield. Uncertain parameters are identified in each of the submodels, and a preliminary parameter sensitivity study is carried out by varying these values to examine their effects on the heat transfer and ablation rates in the coupled problem.

Kenji Miki∗, Marco Panesi∗, Ernesto E. Prudencio†, Andre Maurente∗, Sai Hung Cheung∗, Jeremy Jagodzinski∗, David Goldstein‡, Serge Prudhomme§, Karl Schulz¶, Chris Simmons‖, James Strand∗∗ , and Philip Varghese†† Center for Predictive Engineering and Computational Sciences (PECOS), Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, 1 University Station C0200, Austin, Texas 78712, USA

A procedure has been developed to couple a hypersonic reacting flow model, a radiative heat transfer model, and a surface ablation model to study the surface heat transfer and surface ablation rate of atmospheric entry vehicles. The “loose” coupling algorithm is described for each of the models as well as the solution procedures to achieve convergence. Observations on the challenges of the loose coupling strategy are given. Representative results are presented for 2-D benchmark examples and for flow at angle of attack past an axisymmetric capsule based on the CEV reentry vehicle. Effects due to the interaction with radiation and ablation are shown for two quantities of interest, the predicted peak surface heat flux and the ablation rate on the vehicle heatshield. Uncertain parameters are identified in each of the submodels, and a parameter sensitivity study is carried out by varying these values to examine their effects on the heat transfer and ablation rates in the coupled prediction.

This paper presents the computation of radiation heat transfer in a cylindrical enclosure in which the dimensions, the chemical species concentrations and the temperature fields make a realistic representation of an actual combustion chamber. Two gas models are applied and compared: the absorption-line blackbody distribution function (ALBDF), and the standard weighted-sum-of-gray-gases (WSGG) based on coefficients and correlations that are widely used in engineering. While the standard WSGG is restricted to the assumption of homogeneous gas mixture, the ALBDF can be applied to both homogeneous and non-homogeneous media. For the two gas models, the radiative exchanges are computed with the aid of the Monte Carlo method. The results show considerable discrepancies between the WSGG and the ALBDF models for the homogeneous medium. In addition, the importance of considering the non-homogeneity of the medium for an accurate computation of the radiative heat transfer is shown.