Features Of Thermal Radiation Research Articles

Thermal performance of mixed convective radiative peristaltic flow of Bingham nanofluid

The significance of peristaltic phenomena has generated substantial interest within the fields of biological and biomedical engineering. Therefore, the present study deals with magnetohydrodynamics (MHD) peristaltic flow of Bingham nanofluid in a channel. Here the channel walls are symmetric and elastic in nature. Velocity slip, heat and mass convective conditions are enforced on channel walls. The aspects of dissipation, Joule heating and mixed convection is analyzed. Thermal transport included the features of thermal radiation, Brownian and thermophoresis motion. Analysis and modelling are investigated in the presence of the phenomenon heat generation and absorption. The analysis has been wrapped up under the assumptions of a long wavelength and a low Reynolds number. Numerical techniques are implemented for finding the solutions of governing differential system. Results for velocity, concentration, thermal field, rate of heat transfer, skin friction coefficient, Nusselt number and Sherwood number are analyzed subject to pertinent parameters. The study reveals that velocity is enhanced via both thermal Grashof number and velocity slip parameter. Temperature shows opposite behavior against radiation and Brinkman number. Rate of heat transfer enhances for larger values Brownian motion and Hartman parameters. This study's practical applications include the use of peristaltic pumps for drug delivery in the pharmaceutical and chemical industries.

Magneto-Thermo Heat Transfer of a Chemically Reactive and Viscous Dissipative Casson Nanofluid Thin Film Over an Unsteady Stretching Surface with Variable Thermal Conductivity

This paper addressed unsteady magnetohydrodynamic flow and heat transfer of an incompressible Casson nanofluid thin film past a stretching sheet by considering the features of thermal radiation, chemical reaction, and viscous dissipation. The problem is modeled mathematically, and the governing basic equations are brought into nonlinear ordinary differential equations by utilizing appropriate similarity transformations. Then the transformed equations are then solved numerically by using the bvp4c solver. The influences of pertinent physical variables are performed on velocity, temperature gradient, and nanoparticle concentration gradient profiles. It is seen that the profile of the nanoparticle concentration gradient enhances by increasing the values of the Schmidt number, whereas the opposite trends are observed by increasing the values of the thermophoresis parameter. It is also analyzed that by increasing the values of the thermophoresis parameter, there is an increase in the profiles of the temperature and concentration distributions. The computed results are obtained by giving main consideration to the convergence process and comparing them with the results existing in the literature.

An automatic extraction method for geothermal radiation sources based on an LST retrieval algorithm and semantic network

Geothermal resources are efficient, renewable and clean energy sources, and their reservoirs are usually closely associated with high-temperature regions of the land surface. Current exploration methods primarily involve migrating traditional geological techniques, which fail to fully use the unique features of geothermal radiation characteristics. Thermal infrared remote-sensing imaging technology can capture and present areas with distinctive surface thermal radiation features, providing considerable significance as a guide for localization prior to field exploration. In this study, we propose a deep learning–based method for intelligently identifying and segmenting geothermal radiation sources from thermal infrared remote-sensing images, including data preparation and model training. To improve the localization drift and anomalous interference caused by the high complexity of the Earth's surface environment, this study uses a surface temperature retrieval algorithm to calculate the land surface temperature in the research area. The retrieval results are used to train the semantic segmentation model. In addition, a pixel-level geothermal spatial segmentation network (PGSSNet) is proposed to suppress the diffuse thermal radiation and reduce the broad and blurred white areas of images to exact locations. Once the training is completed, the model directly segments and extracts the actual range of thermal radiation sources from subsequent thermal infrared remote-sensing images without temperature retrieval and/or manual calibration.

Mathematical modelling for peristaltic flow of fourth‐grade nanoliquid with entropy generation

AbstractNanomaterials having excellent thermal properties are employed in producing energy, extrusion processes, engineering processes, nuclear interactions, industrial domains and aero‐spaces, etc. Therefore, current study scrutinizes the aspects of entropy optimization and Ohmic heating on MHD peristalsis of fourth‐grade nanoliquid in a channel. Flexible channel walls retain concentration, thermal slip and velocity conditions. The consequences of viscous dissipation and Arrhenius activation have been accounted. The lubrication approximation is used in mathematical modelling. Nanofluid model is used by considering thermophoresis and Brownian motion. Furthermore, thermal radiation features are included in the energy equation. By using an appropriate similarity transformation, a system of PDEs is simplified to a solvable system of ODEs. Numerical techniques are used to solve the problem of governance. Detailed exploration of the sundry variables of concern on the flow quantities like velocity profile, nanoparticle concentration, temperature and entropy of the system is graphically examined. Heat transfer is examined in tabular form. Based on the derived outcomes, the velocity rises via thermal Grashof and slip variables. Further, an increment in Brownian motion and radiation parameters shows opposite behaviour on temperature.

Kevlar nanofibrous aerogel-based 3-layer tandem cloak enables highly efficient and long-lasting infrared stealth

The control of thermal radiation features of objects for the purpose of infrared stealth has aroused extensive research interests in recent years, however, long-term and highly efficient infrared stealth for hot object under sunlight is still a giant challenge. Herein, a Kevlar nanofibrous aerogel-based 3-layer tandem cloak for long-term restraining of the thermal emission was proposed. The top layer was fabricated by magnetron sputtering silver (Ag) on the upper side of Kevlar nanofibrous aerogel film (Ag|KNA), demonstrating high thermal resistance (8.68 K·W−1), low infrared emissivity (0.12) and high optical reflectivity (0.87). The middle layer was realized by incorporating of phase change paraffin wax (PW) into KNA film (KNA/PW), showing phase change enthalpy of 162 J·g−1. The bottom layer was fabricated by sputtering Ag on the lower patterned side of KNA film (PKNA|Ag), illustrating low infrared transmittance (close to zero), high thermal reflectivity (0.94) and high thermal resistance (10.42 K·W−1). Then flexible tandem cloak was constructed via stacking these aerogel-based top, middle and bottom layers in sequence, showing long-term (up to 12 h), high-efficiency (radiation temperature difference less than 1 °C) hiding of thermo-model targets under heating and sunshining simultaneously. This work provides a promising strategy for designing more practical tandem cloak for infrared stealth applications.

Infrared-visible image fusion method based on sparse and prior joint saliency detection and LatLRR-FPDE

In this paper, a new infrared and visible image fusion method based on saliency detection and LatLRR-FPDE is proposed to ensure the saliency of the fused target and improve the clarity of the texture detail information of the latent low-rank representation (LatLRR) fusion method. In the feature representation stage, source images are decomposed into low-rank and sparse parts based on LatLRR. Then Fourth order Partial Differential Equation (FPDE) is used to extract high-frequency detail information from the low-rank part. In the fusion decision stage, according to the characteristic difference of the decomposed sub-bands, a multi-scale fusion scheme is carried out using rules such as EM (expectation-maximization), average (AVG), and the maximum absolute value. To guarantee the integrity of thermal radiation features in the target area in fusion results, an infrared image saliency detection algorithm is proposed, which utilizes the fusion information obtained from the sparse and prior saliency feature. Specifically, the algorithm uses convex hull center prior and contrast prior to obtain the background-suppressed saliency map. Meanwhile, to make full use of the high-dimensional saliency features in the image decomposition stage, the prior saliency map and the sparse saliency map are fused to improve the accuracy of saliency detection without the demand to extract redundant feature, which largely increases time-efficiency of the model. Finally, infrared feature compensation is performed on the target region of the fused image based on the saliency mapping strategy to make the final fused image having a better infrared target feature representation. The experiments are based on registered public datasets and compared with various popular image fusion algorithms. The subjective and objective results show that the proposed algorithm can effectively keep the integrity of salient infrared features and has superior visual quality.

IVF-Net: An Infrared and Visible Data Fusion Deep Network for Traffic Object Enhancement in Intelligent Transportation Systems

Infrared and visible data fusion (IVF) aims to generate a fused output that simultaneously highlights salient thermal radiation features and preserves texture information, which can not only grasp the necessary information for traffic movement, but also highlight the invisible objects that need to be dodged in intelligent transportation system (ITS). Therefore, IVF is capable of improving the environmental perception ability for various challenging traffic situations, e.g., foggy scenarios, rainy environments, and low-light illumination. However, current available IVF algorithms cannot offer a theoretical manner to integrate a priori knowledge and the network structure into a unified model. Moreover, they always fail to handle infrared and visible data pairs with different resolutions, which is a common occurrence in real ITS scenarios. To this end, this study develops a novel model-inspired unsupervised network termed IVF-Net. Specifically, an enhanced IVF model (IVFM), which pays more attention on detailed texture information and salient objects, is first established. According to proximal gradient theory, then we map this model into a deep network with learnable feature extraction parameters, aiming to draw on the strengths of the fusion model and deep learning to better describe the IVF task. Finally, a multiple task-driven loss function is designed to train the mapped network. Unlike previous work, our IVF-Net is motivated by IVFM, each layer in which has a semantic interpretability and a clear mission, thereby leading to a significantly enhanced fusion effect. Another advantage is that it is only composed of simple convolution-based structures, which ensures its lightweight and efficiency. Experiments demonstrate that IVF-Net can have a stronger ability to capture the key traffic information and highlight the salient feature of imperceptible objects, which makes it an excellent candidate to improve the reliability of subsequent applications in ITS.

Features of Radiative Mixed Convective Heat Transfer on the Slip Flow of Nanofluid Past a Stretching Bended Sheet with Activation Energy and Binary Reaction

The current exploration aims to inspect the features of thermal radiation on the buoyancy or mixed convective fluid flow induced by nanofluid through a stretching permeable bended sheet. The impact of activation energy and binary reaction along with slip migration is taken into account to discuss the fine points of water-based alumina nanoparticle flow. The structure of the curved sheet is assumed to be stretchable and the bended texture is coiled within a circular section with radius Rb. The similarity technique is utilized to reduce the leading partial differential equations into ordinary differential equations. These reduced equations are then deciphered numerically by employing the bvp4c method. The outcomes of the model were constructed in the form of several figures and bar graphs for the case of opposing and assisting flows with varying distinct embedded control parameters. The results display that the velocity field curves escalate with a higher radius of curvature parameter while temperature and concentration profiles shrink. More precisely, the outcomes show that the temperature distribution profile increases with the increase in nanoparticle’s volume fraction as well as thermal radiation parameter. Meanwhile, the concentration and velocity fields are decelerated with higher impacts of nanoparticle volume fraction. In addition, the heat and mass transfer rates were significantly improved for the higher value of the radiation and Schmidt number. On the other hand, the growing values of the velocity slip factor decrease the shear stress. Furthermore, the results are compared with the previous results in the limiting cases and observed a tremendous harmony.

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R2) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

CUMULATIVE IMPACT OF VISCOUS DISSIPATION AND HEAT GENERATION ON MHD DARCY-FORCHHEIMER FLOW BETWEEN TWO STRETCHABLE DISKS: QUASI LINEARIZATION TECHNIQUE

This research describes the irreversibility analysis of steady flow with magnetic effects between two infinite stretching disks situated in a Darcy-Forchheimer medium. The energy equation is amended by the features of thermal radiation and heat absorption or generation. Similarity transformations are employed to transform the formulated equations into dimensionless form. Quasi linearization technique with the application of mathematical computational software MATLAB is used to acquire the numerical solution of these non-dimensional modeled equations. It is noticed that Eckert number, heat generation/absorption and Forchheimer parameter accelerate the temperature, while the radiation parameter decreases the temperature. It can also be observed that axial velocity is affected by inertia as well as porosity of the medium. Moreover, skin friction coefficient is an escalating function of porosity, magnetic and Forchheimer parameters.

Melting effect on Cattaneo–Christov and thermal radiation features for aligned MHD nanofluid flow comprising microorganisms to leading edge: FEM approach

An investigation for fluctuating temperature with Cattaneo–Christov features and self-motive bioconvective microbes immersed in the water based nanofluid has been observing with excision/accretion of the leading edge. A set of partial differential equations is transferring by implementing the similarity measures to an ordinary differential pattern. A finite element technique is employed to establish the numerical results of the set of non-linear system of equations via Matlab programming. The numerical solution's reliability and validity are determined by ascertaining convergence specifications and comparing them to established novel solutions. The formulation of boundary layer configurations for microbes propagation, fluid temperature, the volume fraction of nano-inclusions, and the fluid velocity with varying persuasive parameters have discussed. The main findings of the prevailing assessment are that an increasing trend in the ablation/slash accretion in leading-edge declines in the non-dimensional melting factor of fluid velocity and temperature, while a decreasing trend has seen with the enhancing impact of ablation/slash accretion at the leading edge that represents the flow velocity deceleration. Furthermore, a significant result is that an increase in the non-dimensional melting factor enhances the density of the liquid.

Features of thermal radiation of one-dimensional photonic structures on an absorbing substrate

The dependences of the thermal radiation (TR) lines contrast and amplitude of the systems (photonic structure)/substrate on the optical characteristics of both the photonic structure and the substrate have been investigated theoretically and experimentally. As it has been ascertained, these dependences demonstrate non-monotonic behavior, and the characteristics of the system TR can both increase and decrease depending on the ratio of individual optical parameters of the system components. The results of theoretical research were confirmed by experimental studies of TR systems Ge/GaAs, Ge/GaAs/Al, GaAs/Au and GaAs/(opaque substrate). The results of the research can be used in the development of narrow-band emitters for the middle and far IR range, which can be applied in the optical infrared devices for a wide range of applications.

Features of Cu and TiO2 in the flow of engine oil subject to thermal jump conditions

The recent work investigates the heat transfer attributes in the flow of engine oil which comprises of nano-particles such as Cu and TiO2. The performance of Copper and Titanium oxide is over looked in the flow of engine oil. The energy equation is amended by the features of thermal radiation, viscous dissipation, and heat generation. The mathematical model signifies the porosity, entropy generation and moving flat horizontal surface with the non-uniform stretching velocity. Quasi-linearization, which is a persuasive numerical technique to solve the complex coupled differential equations, is used to acquire the numerical solution of the problem. Flow and heat transfer aspects of Cu–TiO2 in the flow are examined against the preeminent parameters. The flow is significantly affected by the thermal jump conditions and porous media. It is observed here that the temperature as well as heat transport rate is reduced with the effect of involved preeminent parameters. However, such fluids must be used with caution in applications where a control on the heat transfer is required. We may conclude that the recent study will provide assistance in thermal cooling systems such as engine and generator cooling, nuclear system cooling, aircraft refrigeration system, and so forth.

Magnetohydrodynamic mixed convection 3-D simulations for chemically reactive couple stress nanofluid over periodically moving surface with thermal radiation

In the recent advancement in growing nano-technology, the dynamic scientists have shown their interest toward the thermal aspects of nanoparticles due to their prestigious industrial, engineering, medical and modern sciences applications. The current exertion discloses unsteady three-dimensional chemically reactive couple stress nanofluid flow induced by bidirectional oscillatory stretching surface. The heat transfer analysis is explored by utilizing heat generation/absorption and thermal radiation features. Additionally, the mixed convection and magnetic effects are also encountered as novelty. The flow has been generated by bidirectional periodically accelerated surface. Apposite transformations are engaged to reduce formulated nonlinear problem into dimensionless form, and then analytic series solution is computed via homotopic technique. The physical aspect of involved flow parameters is graphically entertained. A complete graphical investigation for profiles of dimensionless velocities, temperature, concentration and skin friction coefficients is deliberated for various prominent flow parameters. Furthermore, the numerical calculations for local Nusselt and Sherwood numbers are presented and discussed. The results perceived that amplitude of oscillation increases in both components of velocities and skin friction coefficients for higher couple stress parameter. It is further reported that temperature distribution enhanced for higher values of Brownian motion parameter, thermophoresis constant and radiation parameter. Moreover, the concentration distribution decreases for enhancement of Brownian motion parameter and chemical reaction parameter.

Simulation of magnetic dipole on gyrotactic ferromagnetic fluid flow with nonlinear thermal radiation

The present paper explores the features of thermal radiation on ferromagnetic Jeffrey fluid flow within the frame of gyrotactic microorganisms and magnetic dipole. Microorganism is employed just to stabilize the suspended nanoparticles through bioconvection which has been induced by combined effects of buoyancy forces and magnetic field. Nonuniform heat generation/absorption, stratification, dissipation and chemical reaction are accounted. The attained system is solved numerically by means of the shooting method in conjunction with Runge–Kutta method (RKF-45). The obtained numerical results are then presented in graphical and tabular form and are discussed at length. In addition, the validation of present outcomes is achieved by developing comparison with existing published work. The present analysis reveals that the temperature profile enhances in view of radiation and ferrohydrodynamic interaction parameters. Moreover, space- and temperature-dependent heat absorption are more suitable for cooling purposes.

Bioconvection flow of magnetized Carreau nanofluid under the influence of slip over a wedge with motile microorganisms

This article addresses the time-dependent flow of magnetized rheological Carreau nanoliquid conveying microorganisms over a moving wedge with velocity slip and thermal radiation features. Carreau fluid is auspicious to depict several types of physical issues because this fluid model has the capability of revealing the rheology of multiple specific fluids such as fluids with brief-chain suspension particles, fluid crystals, detergents, and blood in animals and humans. The mathematical formulation is developed by combining the impact of infinite shear rate viscosity. The physical aspects for both static and moving are discussed in detail. At first, relevant similarity transformations are employed to obtain dimensionless form of equations, and then renovated equations have been solved numerically by employing bvp4c via MATLAB based on shooting technique. Both the numerical and graphical results against physical quantities, such as velocity temperature, nanoparticles concentration and density of gyrotactic microorganism, are observed under the influence of physical parameters.

Effects of nonlinear thermal radiation and activation energy on modified second-grade nanofluid with Cattaneo–Christov expressions

The aim of the current contribution is to exploit the effects of nonlinear thermal radiation and activation energy on the flow of modified second-grade fluid with the utilization of nanoparticles. The induced flow has been considered by linear movement of stretched surface which is considered to be porous. Famous modified second-grade fluid enables one to capture the important rheological features of shear thinning and thickening. Following the modern aspects of heat and mass transportations, we have employed the theories of Cattaneo–Christov heat flux and generalized Fick’s relations. The additional features of thermal radiation are also utilized in the energy equations with nonlinear expressions. Further, the impact of activation energy is also considered in the current continuation which makes the study quite versatile. While operating the suitable variables, the constituted problem has been distracted in a dimensionless form. The solution procedure has been followed with the implementation of the famous shooting technique with desirable accuracy. The involved engineering parameters are explained graphically with interesting physical consequences. It is noted that velocity distribution declined with a stretching ratio constant and combined parameter. An improved nanoparticles temperature distribution is observed with increases in stretching parameter and Brownian motion constant. The study also reports that the presence of activation energy can be more useful to enhance reaction processes. Based on the obtained scientific computations, it is claimed that the reported results can play a useful role in manufacturing processes and improvement in energy and heat resources.

Thermally developed unsteady viscoelastic micropolar nanofluid with modified heat/mass fluxes: A generalized model

The main concern of current investigation is to develop an unsteady mathematical model for viscoelastic micropolar nanofluid flow caused by periodically accelerating surface. The generalized heat and mass flux relations are utilized in the energy equation. Further, the energy equation is altered by employing thermal radiation features derived from famous theory of Rosseland’s approximation. The Prandtl number and radiation constants are premeditated as new parameter called here as effective Prandtl number. The solution of formulated dimensionless equations has been stimulated with the help of homotopy analysis method. A theoretical based observation for each engineering parameters is carried out with detailed physical properties. The involved physical quantities namely effective Nusselt number and Sherwood number are evaluated numerically. Numerous contributions have been advised for flow of micropolar fluid but no attempt has been made regarding unsteady viscoelastic micropolar nanofluid with Cattaneo–Christov model which may eventually reduced to the traditionally viscous, viscoelastic and micropolar fluid results simultaneously as limiting cases.

Chemically reactive bioconvection flow of tangent hyperbolic nanoliquid with gyrotactic microorganisms and nonlinear thermal radiation

On the account of motivating fabrication of bioconvection phenomenon in various engineering and industrial systems, an attention has been devoted by researchers in current decade. Therefore, this theoretical investigation deals with the utilization of bioconvection phenomenon in flow of tangent hyperbolic nanofluid over an accelerated moving surface. It is assumed that the flow is generated due to periodically motion of the sheet. The energy equation is modified by entertaining the nonlinear thermal radiation features. The chemical reaction effects are elaborated in the concentration equation. Moreover, the significance of present flow problem increases by utilizing the thermophoresis and Brownian motion effects. The governing equations are transmuted into non-dimensional form with utilization of appropriate quantities. The analytical solution is computed by using homotopy analysis method. The implications of promising parameters on velocity profile, temperature profile, nanoparticles volume fraction and microorganisms profile is evaluated graphically. The presence of radiation parameter, thermophoresis and Brownian motion effects are more frequent for enhancement of heat transfer. The reported observations can efficiently use in the improvement of heat transfer devices as well as microbial fuel cells.

Theoretical analysis of cross-nanofluid flow with nonlinear radiation and magnetohydrodynamics

In this article, the characteristics of physical model steady axisymmetric flow of cross-fluid over a stretching sheet are explored numerically. Furthermore, steady flow of nanofluid is expressed by means of Buongiorno’s model for nanoparticles. Moreover, the features of thermal radiation and chemical reaction processes with partial velocity slip condition are adopted here. Nonlinear PDEs are converted to ODEs using suitable transformation variables. The reduced systems of ODEs are resolved using an effective bvp4c scheme implemented. Numerical computation for physical parameters such as skin friction, Nusselt and Sherwood numbers are also examined. Magnetic field plays a vital role in controlling the flow of fluid and has the tendency to enhance the thermal boundary layer and concentration. Similarly, skin friction, Nusselt and Sherwood numbers depreciate by improving the values of velocity slip parameter, magnetic parameter, magnetic parameter, thermophoresis parameter in shear thickening fluids.