Radiative Heat Transfer Research Articles

CFD simulations of helium layer erosion in one PANDA vessel following cooler activation

We performed CFD simulations of the two H2P6 cooler tests conducted in the PSI PANDA vessel as part of the OECD/NEA HYMERES-2 project. Initially, the vessel atmosphere consists of a 60/40 % vol. steam- air mixture. Then, a helium stratification (15 % vol.) is introduced in the upper half of the vessel. The two experiments H2P6_1 and H2P6_2 are characterized by the activation respectively of 3 and 1 cooler(s) in the upper part of the vessel. In the course of the experiments, condensation takes place, resulting in a gradual pressure decay and erosion of the helium layer until complete mixing is achieved.The URANS k-ε is used to model turbulence. CFD Best Practice Guidelines are followed to minimize numerical errors, with preliminary mesh sensitivity studies. A correlation based on the heat-and-mass transfer analogy is employed to estimate steam condensation rates.Each cooler consisting of 18 tubes is simplified into a cuboid with equivalent heat transfer area. In a further simplification, it is assumed that the cooler wall has a thickness of zero and is initially at the temperature of the coolant. The small initial energy stored in the mass of the cooler at time zero is therefore neglected.The simulation for H2P6_1 matches the main experimental parameters (heat removal rate, pressure, species concentrations) almost perfectly. For H2P6_2 the heat removal rate is slightly under-predicted, with a corresponding over-prediction of the pressure by a maximum of 3 %. The inclusion of radiative heat transfer modeling improves the accuracy of the temperature field but has little influence on the pressure or heat removal histories.These results show that CFD allows accurate predictions of containment mixing when coolers are activated. Moreover, the simulations also indicate that multiple cooler units can be represented by one larger equivalent unit.

On convection vive in mixing-controlled combustion with thermal barrier coatings

Thermal barrier coatings (TBCs) could improve the efficiency of internal combustion engines by reducing heat losses. TBC modeling has demonstrated efficiency gains at all loads in compression ignition, including in gasoline compression ignition (GCI). However, after GCI testing of 13 coated pistons of various materials, thicknesses, and surface preparations in this work, a clear trend was observed: TBCs result in an efficiency gain at 6 bar IMEPn (low load) and an efficiency penalty at 15 bar IMEPn (high load). This can be explained by “convective vive”, which was originally presented by Woschni for engines with TBCs. Convection vive refers to a reduction in the quench distance of a reacting flame when the quenching surface temperature is elevated, resulting in an increased heat transfer coefficient and heat transfer rate despite the lower temperature difference between the gas and the wall. Although this work is unable to provide direct experimental evidence for convection vive, several experiments were performed to rule out alternate theories including differences in heat release rate, radiation heat transfer, combustion chamber deposits, and surface catalytic effects. Experiments also showed that at 6 bar IMEPn, injection pressure did not impact the performance of the TBC compared to the metal baseline, but at 15 bar IMEPn, the efficiency penalty increased with rail pressure. These results provide indirect evidence of convection vive: as the surface temperature of the TBC increases with load past a threshold, the quench distance decreases to the point where exothermic reactions can occur in the boundary layer, which raises the convective heat transfer coefficient. This implies that in mixing controlled combustion systems, the TBC should not be present on combustion chamber surfaces that experience high fuel-wall interaction during combustion.

Large-scale PANDA facility – radiation experiments and CFD calculations

Abstract CFD modelling of the thermo-hydraulic phenomena in the containment during the various phases of a severe accident necessarily requires consideration of radiative heat transfer – in the presence of steam. These radiative phenomena include (i) energy transfer within the gas mixture and (ii) between the gas and surrounding structures. Preliminary calculations carried out for these types of experiments within the OECD/NEA HYMERES-2 project with the CFD code containmentFOAM using a Monte Carlo solver for thermal radiation, demonstrated that the radiative heat transfer is significant even for very small amounts of vapour in the range of ≈0.1 % to ≈2 %. For this reason, the test matrix was tailored to the two opposite extremes: either gas compositions with a low vapour/steam content, where radiative heat transfer can be neglected, or gas mixtures with higher vapour contents, so that radiative heat transfer plays a dominant role. For the selected experiments of the H2P2 series and the corresponding CFD calculations, a vessel with a diameter of 4 m and a height of 8 m was preconditioned with different air-vapour mixtures (a) at room temperature and (b) elevated temperatures. A stable helium layer was then built-up in the upper part of the vessel. The gas was then compressed by injecting helium from above which resembles with best efforts a compression with a piston in a cylinder. This results in a height-dependent and transient increase of the gas temperature. These experiments and the associated CFD calculations were developed to isolate the phenomena of thermal radiation as good as possible from convective and diffusive effects – within the always present experimental limitations. For the reference experiment with ‘dry conditions’ corresponding to the lowest experimentally possible humidity of ≈0.1 %, we show that the use of a model without radiation provides the best agreement between the experimental and numerical results. For the much higher steam content of ≈60 %, the statistical narrow band correlated-k model (SNBCK), non-gray gas model, is the best candidate for future calculations – with computationally forgivable additional effort. We also provide with the Filtered Rayleigh Scattering technique (FRS) an outlook for a possible future instrumentation approach to better meet the requirements of the CFD community.

Numerical investigations and design optimization of cryogenic plate-fin heat exchanger in Electric Arc Furnace using radiative heat transfer model

The most crucial element affecting cryogenic systems’ energy efficiency is heat exchangers. In this article, a model for cryogenic plate-fin heat exchanger (PFHE) under thermal-hydraulic performance with various blends is proposed. To reduce five objective functions total heat transfer rate, total weight, total mass flow rate, number of entropy generating units, and whole annual cost the study carried out the PFHE’s optimal design. This study innovatively focuses on optimizing PFHE design for cryogenic conditions using Opposition Learning with the Beetle Swarm algorithm. The proposed geometry addresses non-uniform temperature distribution, emphasizing thermal-hydraulic properties in various blends. Additionally, a second-order semi-discretization radiative heat transfer approach enhances boiler simulation accuracy. A multi-objective optimization of Opposition Learning with Beetle Swarm (MO-OBBS) optimization approach was suggested in the article for the design of PFHE. Despite the significant potential for renewable energy the low-temperature waste heat treatment process is rarely examined from a sustainability perspective. Consequently, the study proposed a second-order semi-discretization radiative heat transfer method to simulate a furnace using a water heat recovery process. The cooling panel’s numerical analysis was conducted using computed temperature fields. The performance of the various algorithms is compared using the Freidman rank-sum test to determine the statistical significance of the findings obtained. In logarithmic coordinates, the proposed method’s faster convergence is compared to GQB-PSO, SLTLBO, Jaya, CKKO, and OLE-SCA algorithms. The proposed method exhibits a maximum average increase of 115.39% for PFHE design. When the numerical simulation results are compared to measurements of output water temperature, the accuracy is highly improved.

Influence of the greenhouse effect on heat transfer through building envelopes

The evaluation of heat input through fences is an important part of the task of predicting the summer thermal regime of a building under a transparent dome, the interest in the construction of which in the northern regions has increased recently. The calculation of the summer thermal regime of a building under a dome is complicated by taking into account the greenhouse effect, which requires solving the problem of radiative heat transfer in the system: opaque wall - semitransparent screen - environment. It is also necessary to take into account the convection in the dome space. А relatively simple model for calculating the characteristics of heat transfer through the wall of a building with a dome, which takes into account the greenhouse effect, is considered in this paper. Comparison of calculations with experimental data allows us to speak about the adequacy of the proposed model. It is shown that the presence of semitransparent screen due to the greenhouse effect leads to a significant raise in temperature under the dome and an increase in heat input into the building. The influence of ventilation in the dome space on heat access through the enclosing structure for the selected values of external parameters: external temperature and solar radiation was evaluated. The proposed model of heat transfer through the enclosing structure with a semitransparent screen can become part of a more complete model for calculating the thermal regime of a building under a dome.

Numerical study of near-field radiative heat transfer between bio-inspired spiny particles

The spine-like structure appears on some smooth organisms and has a high light absorption cross-section. Inspired by the spiny structure in the nature, this study establishes models of solid and hollow spiny particles. The effects of spine cross-section size, uniform and nonuniform spine distribution, hollow size, gap, and spine dislocation on near-field radiative heat transfer of spiny particles are investigated based on the thermal discrete dipole approximations method. The spectral radiative conductance and volumetric net power distribution are obtained. The results indicate that the coupling of localized surface phonons between two particles is affected by spine cross-section size and spine distribution. Near-field radiative heat transfer of spiny particles is enhanced maximumly when the frequencies are slightly lower than the resonance frequency of smooth particles. The peak of the spectral conductance is red-shifted and decreases with the increase of hollow size. The uniformity of volumetric power absorbed distribution increases and the variation of the relative spectral conductance decreases with increasing gap. The influence of two particles’ spine dislocation on near-field radiative heat transfer and volumetric power absorbed distribution is not obvious.

Effects of ignition location on CH4/air explosion characteristic in a spherical bomb

To build methane anti-explosion storage equipment, the influence of the ignition location on the CH4/air explosion in a spherical equipment was investigated. A two-step CH4/air reaction mechanism was developed and it considered the effect of heat transfer on the explosion. The effect of methane explosion pressure on heat loss was studied. The results show that the maximum explosion pressure of central ignition is 0.72 MPa under the heat loss simulation. The peak pressure of the upper and lower end-wall explosion is about 79.2 % and 83.3 % of the central ignition explosion, respectively, and the experimental results verifies the simulation results. Therefore, the reason for the highest peak pressure of central ignition methane explosion is that the reaction speed of central ignition methane explosion is the fastest, and the heat loss is the lowest. The difference in peak pressure between the upper and lower wall surfaces is due to the buoyancy effect accelerates the reaction rate of the lower end-wall ignition. In the simulation time range, the heat radiation at different ignition locations accounts for more than 70 % of the total heat loss, and radiation heat transfer plays a leading role in the total heat loss.

Performance evaluation and parameter optimization of tubular direct absorption solar collector with photothermal nanofluid

Photothermal nanofluids exhibit broad-spectrum absorption characteristics, rendering them highly promising for applications in direct absorption solar collector (DASC). A three-dimensional computational fluid dynamics (CFD) model is established to analyze the solar collection performance of a tubular DASC. Three distinct types of nanofluids used in direct solar absorption collector have been investigated, employing the Rayleigh scattering method to compute their optical parameters. The non-gray discrete ordinates radiation method is employed to solve radiation heat transfer within the glass wall and nanofluid. The findings reveal that graphite nanofluids exhibit the most favorable thermal performance among the tested nanofluids. The impact of different operating parameters, such as mass fraction and flow rate, on the thermal performance of the tubular DASC is elucidated through thermal and exergy efficiency analyses. The results indicate that thermal performance experiences only marginal changes when the mass fraction exceeds 50 ppm. Thermal efficiency increases with higher mass flow rates, while exergy efficiency displays an inverse relationship. This research contributes valuable insights that can guide the selection of suitable working mediums and the optimization of operational parameters for DASC system.

Experimental and Computational Study of the Thermal Insulation Properties of Hollow Glass Microspheres

Hollow glass microspheres (HGM) are expected to be used in cryogenic liquid storage tanks as an insulating material with better insulation performance and lower maintenance cost instead of perlite. Obtaining the effective thermal conductivity of HGM can help to improve the insulation performance of cryogenic tanks. Herein, a test system based on the transient plane source method is designed and constructed, and the effective thermal conductivity of six models of HGMs from four suppliers at 200–300 K is measured. The results show that under atmosphere pressure of 200 K, the effective thermal conductivity of HGM is only 25.87–35.84 mW m−1 K−1. The effective thermal conductivity at room and low temperatures is calculated using the derived system of equations for integrated thermal conductivity and radiative heat transfer, with the error of no more than 13% from the current experimental results. The integrated thermal conductivity is still dominant in low pressure and low temperature, and the reduction of the true density contributes to the improvement of the HGM insulation performance.

Parameters effect and optimization on calciner for treating magnesium salt based on computational fluid dynamics

The magnesium salt Mg(NO3)2·2H2O from laterite nickel ore nitric acid leaching process can be reused by thermal decomposition using calciner. To improve the performance of the calciner, a new numerical model integrating the gas-particle hydrodynamics and the particle pyrolysis reaction was established by Euler-Lagrange approach. In particular, the particle size variation caused by pyrolysis reaction was considered to accurately describe the gas-particle hydrodynamics. The particle pyrolysis model was developed to realize the interphase mass transfer. The P-1 model was modified to realize interphase radiation heat transfer. Then, the influence of different parameters on the thermal decomposition processes was discussed by using the established model. Finally, the optimal conditions for Mg(NO3)2·2H2O thermal decomposition were determined via response surface optimization analysis. The results show that the thermal decomposition of Mg(NO3)2·2H2O can be improved by increasing the initial hot gas temperature, reaction zone height, and decreasing treatment capacity of Mg(NO3)2·2H2O. The degree of influence of each parameter on thermal decomposition follows the order of initial hot gas temperature > treatment capacity of Mg(NO3)2·2H2O > reaction zone height. The decomposition rate of 99.99 % is obtained at optimized conditions of initial hot gas temperature 1111 K, Mg(NO3)2·2H2O treatment capacity 251 kg/h and reaction zone height 9 m.

Neural network and thermodynamic optimization of magnetized hybrid nanofluid dissipative radiative convective flow with energy activation

This article, motivated by hybrid magnetic coating manufacturing developments, utilizes a neural network-based computational program to study the dynamics of hybrid magnetic nanofluids with entropy generation. A new physico-chemo-mathematical model has been presented to simulate the hybrid magnetic nano-coating flow along a stretching surface to a porous medium with viscous heating. A Rosseland flux model is used for radiation heat transfer and Darcy’s model for the isotropic porous medium. The stretching sheet is porous, and wall suction or injection are possible. A robust neural network has been deployed to optimize the physical parameters controlling the transport characteristics of hybrid nanofluids. Specifically, two hybrid nanoparticle combinations are addressed, namely graphite oxide (GO)-molybdenum disulfide ( Mo S 2 ) and copper (Cu)-silicon dioxide ( Si O 2 ), both with engine oil as the base fluid. The dimensional boundary layer model is transformed via suitable scaling variables from a partial differential system into a dimensionless non-linear coupled ordinary differential system. The transformed boundary value problem is solved numerically with the BVP4C subroutine in the symbolic software MATLAB, which achieves exceptional accuracy. Validation with previous simpler studies is conducted and a good correlation is obtained. The neural network optimization analysis incorporates Bayesian regularization as the training algorithm. The Bejan entropy generation minimization (EGM) analysis shows that with increasing radiation parameter R d , both entropy generation rate and Bejan number are increased. Furthermore, an elevation in Brinkman number Br leads to an upsurge in entropy generation rate and a downtrend in the Bejan number. The numerical solution of the boundary value problem reveals that with an increment in nanoparticle solid volume fraction φ 2 , magnetic parameter M , inverse permeability parameter ϵ , surface injection parameter ( s < 0 ) , Eckert number Ec and radiation parameter R d and with a decrement in suction parameter ( s > 0 ) and Prandtl number Pr , there is a strong enhancement in temperature magnitude and thermal boundary layer thickness. With greater nanoparticle solid volume fraction φ 2 , magnetic parameter M , inverse permeability parameter ϵ , suction parameter s and a reduction in thermal buoyancy parameter λ , strong flow deceleration is induced, and momentum boundary layer thickness is increased. The skin friction coefficient is substantially boosted with lower values of magnetic parameter M , inverse permeability parameter ϵ , suction parameter s and higher values of thermal buoyancy parameter λ . There is a significant decrement also computed in Nusselt number with a greater radiation parameter R d . The simulations provide a good benchmark for future extensions that may consider non-Newtonian behavior.

Anisotropic and hierarchical biphasic nanorod ceramic aerogels with thermal radiation shielded, high strength and exceptional stability for thermal superinsulation

The utilization of ceramic aerogels is crucial in spacecraft thermal protection systems that necessitate exceptional high-temperature stability, mechanical robustness, and low thermal conductivity. The primary challenges hindering their implementation encompass inadequate mechanical robustness and high infrared radiation transparency. Herein, a biphasic nanorod encapsulation strategy is proposed to fabricate an Al2O3-TiO2 nanorod aerogel (ATNA) with a hierarchical and anisotropic microstructure. The biphasic nanorod structure not only reduces the radiation heat transfer but also enhances the mechanical properties simultaneously. The primary compressive strain was borne by the intersecting Al2O3 nanorods, while the interpenetrated TiO2 nanorods served to reinforce and withstand partial stress at the joints. The ATNAs obtained exhibit an ultralow thermal conductivity (0.069 W·m−1·K−1 at 1100 °C), exceptional high stiffness (a specific compressive strength of 13.4 kN·m·kg−1), and remarkable thermal stability (1400 °C in air). The robust ATNAs can effectively meet the urgent demand for thermal insulation in high-temperature environments.

Spectral effects of radiating gases and soot on an experimental aero-engine combustion chamber using full-spectrum k-distribution method

Radiative heat transfer is the main mode of heat transfer and has been proven to be important in the aero-engine combustion. Those radiating gases and soot resulted from combustion may display very strong spectral, or “nongray” behavior, which is difficult to both characterize and evaluate. In this work, the full-spectrum k-distribution (FSK) method is employed to resolve the spectral behavior of both radiating gases and soot during combustion in an experimental aero-engine. Different FSK-based spectral treatments are combined to illustrate how the spectral behavior affects the aero-engine combustion. Those weighted-sum-of-gray-gases (WSGG) results previously done by the authors (Wang, et al. 2024) are also partially compared to the FSK results in this work. Results show that different FSK-based spectral treatments result in small differences for temperature distribution of the flow field. However, since different spectral models are found to impose a considerable effect on radiative heat transfer rate, it is inferred that spectral behavior may be deeply coupled with the generation of pollutants. Results also show that the wall temperature of the combustor liner is highly affected by the spectral model: ignoration of soot radiation underestimates the wall temperature while assuming soot to be gray overestimates the wall temperature. Therefore, high-fidelity spectral models are recommended during the modelling of aero-engine combustion.

Analysis of radiative mixed convective heat transfer for non-Newtonian fluid with heat generation/absorption phenomena

The current work consists of investigating the heat generation/absorption and non-linear thermal radiation effects for two-dimensional mixed convective bi-viscosity fluid flow inside the C-shaped enclosure with uniformly heated left and linearly heated top and bottom walls. The physical flow problem is governed by applying the constitutive laws of bi-viscosity model, conservation of mass, momentum and energy balance equations. The governing non-linear coupled partial differential equations is transformed into the algebraic nonlinear system by using Galerkin's finite-element technique after eradicating the pressure terms via the penalty method, and then the Newton–Raphson technique is used to solve it. It is noted that at a low value of [Formula: see text] (which gives the high plasticity of the bi-viscosity liquid), only the primary circulations with intensity [Formula: see text] appeared, but at a high value of [Formula: see text] decreased the plasticity which caused enhanced buoyancy-driven that generate also the secondary bowls with intensity [Formula: see text] inside the enclosure. The heat transfer rate increased [Formula: see text] by an increase in the Reynolds number from [Formula: see text] to [Formula: see text]. The findings of this study will play a role in improving the thermal performance of microelectronic devices, cooling systems, food processing, solar collectors, and high performance boilers by tracing the energy transport trajectories through heatlines.

Adjoint-based shape optimization for radiative transfer in porous structure for volumetric solar receiver

Due to their large surface areas, porous structures are often used for volumetric solar receivers for efficient utilization of the solar energy. However, the precise simulation and optimization of radiative heat transfer inside porous structures are still challenging due to their complex geometries. In the present study, an adjoint-based shape optimization framework for radiative transfer in porous structures is first proposed. Specifically, an arbitrary complex geometry of a porous structure is represented by a level-set function embedded in a Cartesian grid system. The volume penalization method combined with the discrete ordinate method is employed to simulate a forward radiative transfer problem in a porous structure. Then, a cost functional for an adjoint analysis is defined by the volume average of the divergence of the radiative heat flux, which corresponds to the total heat absorbed by the porous structure with a negative sign. The adjoint equations for minimizing the cost functional, and the corresponding shape update formula are derived and implemented in an open-source software, OpenFOAM. The developed adjoint-based shape optimization framework is applied to three types of initial porous structures, i.e., SC Kelvin, BCC Kelvin, and square honeycomb models. For all the initial porous models, the front surface commonly extends towards the direction of the incident radiation, and consequently notable improvements of the absorption efficiency can be achieved through the optimization. In addition, a systematic parametric survey for the initial shape of the SC Kelvin model is conducted to reveal the impacts of the number of unit cells, the solid emissivity, and the solid temperature on the optimal shapes and the resulting absorption efficiencies.

Pool Fires Within a Large Under-Ventilated Environment: Experimental Analysis and Numerical Simulation Using OpenFOAM

Experimental analyses and numerical simulations are carried out on a test case involving an heptane pool fire within a large under-ventilated environment. During the experiments, the temperature history at several locations within the room is monitored by means of thermocouples, and the fire radiative heat transfer estimated through a plate thermocouple. The experimental layout is then replicated numerically and tested using OpenFOAM CFD code. The study is a preliminary analysis performed for code validation purposes on a full-scale fire scenario. The results of the simulations are compared to the experimental results and critically analysed, finding a reasonable agreement overall. Critical issues in fire modelling are also highlighted. In fact, due to the problem complexity and the limitations of the numerical models available some important aspect that can significantly influence the outcome of the simulations must be calibrated a posteriori, somewhat limiting the general predictive applicability of the fire models. Primarily, these are the heat release rate history, the combustion efficiency, and, to a lesser extent, the convective heat transfer boundary condition at the wall.

The significance of radiative heat and mass transfer through a vertical sheet with chemical reaction: Designing by artificial approach Levenberg-Marquardt

The present study examines the impact of incorporating soft computing algorithms during neural network training on the evaluation and prediction performance of artificial neural networks. The research centers on a magneto hydrodynamic flow model (RHMT-VSCR) that depicts the movement of rotating fluid along a vertical sheet in a permeable medium. Furthermore, the model considers the impact of heat source-sink interactions, thermal radiation, and reactive species in conjunction with the effects of Hall current on the enhancement of energy and solute profiles. Because the induced magnetic field has a negligible magnetic Reynolds number, it is disregarded. A set of governing nonlinear PDEs is converted to a system of ODEs by applying an appropriate postulate of similarity variables in order to analyze the system. The multilayer perceptron network utilizes a supervised Levenberg–Marquardt Backpropagation algorithm (LMLA-BPNN) to ascertain the ideal quantity of neurons to be included in the hidden layer of artificial neural networks intended for modeling purposes. The bvp4c numerical approach is utilized to establish a continuous neural network mapping, which produces datasets that are utilized for the purposes of authentication, training, and testing. The range i.e., 10−2−10−8 of absolute error of the reference and target data demonstrates the optimal accuracy performance of LMLA-BPNN networks. After acquiring knowledge of neural network mapping, it is applied to approximate solutions for a wide range of scenarios through the manipulation of physical constraints, including suction/injection quantities, magnetic parameter, and porosity parameter, which influence the characteristics of flow, energy, and concentration.To assess the precision of the proposed method, statistical graphs based on regression, mean squared error analysis graphs, and error histogram graphs are employed. The results of the research demonstrate that the Levenberg-Marquardt Backpropagation neural network mappings' derivation, convergence, authentication, and stability were effectively validated.

Development of a continuous reheating furnace state-space model based on the finite volume method

This study developed a modeling approach of a continuous steel slab reheating furnace process as a particular case of spatially distributed parameter systems involving radiative heat transfer. The aim of the resulting mathematical model, which is both detailed and computationally tractable, is to serve in prospective advanced process control (APC) and model-based optimization. The two-dimensional state-space model is introduced to accurately simulate the temperature distribution and dynamics, using the finite volume method (FVM) to incorporate essential heat transfer phenomena, including radiation, conduction, convection, advection, and simple combustion. The study presents a novel furnace measurement model that interprets temperature sensor readings (useful for state estimation), a benefit of the FVM treatment of radiative heat transfer. Strategies for linearization and model order reduction, such as balanced truncation, are proposed to facilitate real-time control. The simulation case study demonstrates the targeted capabilities of the model. The accuracy of the model is verified through comparisons with more complex computational fluid dynamics (CFD) software models. The study prioritizes theoretical modeling over empirical validation of a specific furnace unit, omitting experimental validation at this stage.

MHD radiative natural convective heat transfer enhancement for Casson nanofluid flow on a horizontal circular cylinder

The current numerical analysis investigates the sensitivity of heat transfer enhancement in the magnetohydrodynamic radiative natural convection flow of a Casson nanofluid over a cylinder, which has significant ramifications for different fields of science, e.g., biomedical devices, aerospace engineering, nanofluid-based cooling systems, energy harvesting devices, and drag reduction in marine engineering. The effects of numerous physical parameters on heat transfer characteristics are investigated using numerical and statistical simulations. Here methanol is taken as the base Casson fluid, while enhancement is achieved by introducing the nanoparticles such as graphite oxide, along with single-wall carbon nanotubes and multi-walled carbon nanotubes. The transformed governing differential equations are numerically solved using a second-order accurate implicit finite difference scheme known as the Keller-Box technique. To conduct the sensitivity analysis RSM is used to explore the impact of various physical quantities on heat transfer. The influence of Nusselt number (Gr−1/5Nu) and skin friction (Gr1/5Cf) against various physical quantities associated with the behaviour of Casson nanofluid flow are shown in terms of graphs and tables. One of the key findings is that an increase in the Casson parameter leads to a reduction in Gr1/5Cf and an increase in the Gr−1/5Nu. Moreover, among the nanoparticles studied, multi-walled carbon nanotubes prove to be the most effective in enhancing heat transfer.

Generative adversarial networks for data-scarce radiative heat transfer applications

Abstract Generative adversarial networks (GANs) are one of the most robust and versatile techniques in the field of generative artificial intelligence. In this work, we report on an application of GANs in the domain of synthetic spectral data generation for data-scarce radiative heat transfer applications, an area where their use has not been previously reported. We demonstrate the proposed approach by applying it to an illustrative problem within the realm of near-field radiative heat transfer involving a multilayered hyperbolic metamaterial. We find that a successful generation of spectral data requires two modifications to conventional GANs: (i) the introduction of Wasserstein GANs (WGANs) to avoid mode collapse, and, (ii) the conditioning of WGANs to obtain accurate labels for the generated data. We show that a simple feed-forward neural network (FFNN), when augmented with data generated by a CWGAN, enhances significantly its performance under conditions of limited data availability. In addition, we show that CWGANs can act as a surrogate model with improved performance in the low-data regime with respect to simple FFNNs. Overall, this work contributes to highlight the potential of generative machine learning algorithms in scientific applications beyond image generation and optimization.