Thermal Parameters Research Articles

Deep learning the intergalactic medium using lyman-alpha forest at 4 ≤ z ≤ 5

Abstract Unveiling the thermal history of the intergalactic medium (IGM) at 4 ≤ z ≤ 5 holds the potential to reveal early onset He ii reionization or lingering thermal fluctuations from H i reionization. We set out to reconstruct the IGM gas properties along simulated Lyman-alpha forest data on pixel-by-pixel basis, employing deep neural networks. Our approach leverages the Sherwood-Relics simulation suite, consisting of diverse thermal histories, to generate mock spectra. Our convolutional and residual networks with likelihood metric predicts the Lyα optical depth-weighted density or temperature for each pixel in the Lyα forest skewer. We find that our network can successfully reproduce IGM conditions with high fidelity across range of instrumental signal-to-noise. These predictions are subsequently translated into the temperature-density plane, facilitating the derivation of reliable constraints on thermal parameters. This allows us to estimate temperature at mean cosmic density, T0 , with one sigma confidence, $\delta {\rm T_{\rm 0}}\,$≲ 1000K, using only one 20h−1cMpc sightline (Δz ≃ 0.04) with a typical reionization history. Existing studies utilize redshift pathlength comparable to Δz ≃ 4 for similar constraints. We can also provide more stringent constraints on the slope (1σ confidence interval, δγ ≲ 0.1) of the IGM temperature-density relation as compared to other traditional approaches. We test the reconstruction on a single high signal-to-noise observed spectrum (20h−1cMpc segment), and recover thermal parameters consistent with current measurements. This machine learning approach has the potential to provide accurate yet robust measurements of IGM thermal history at the redshifts in question.

Thermal environment analysis and parameters optimization of a novel hot-air phase change heating bed

Maintaining indoor heating consumes significant energy; personalized heating can reduce this consumption. Existing bed-based heating devices have drawbacks in terms of temperature distribution and susceptibility to weather influences. In this paper, a hot-air phase change heating bed (HAPCHB) is proposed, which can heat the indoor thermal environment during the day and the bedding thermal environment at night. The theoretical analysis and simulation model of the new heating bed is established, and the experimental platform for analyzing the thermal environment building effect is built, which verifies the accuracy of the numerical simulation results. The experimental and simulation results show that the thermal inertia of the envelope has a great influence on the room temperature, but has little influence on the bed board temperature under the experimental conditions. Both indoor and bed board temperatures can keep the lower limit of thermal comfort for 12 h continuously. With the increase of phase change material (PCM), the thermal performance of the system is enhanced and attenuated, and the thermal performance of PCM-1.4 scheme is better. The rate of indoor temperature drop is similar under three heating times, but the performance of room temperature and bed board temperature is better at 6 h and 8 h respectively. The research results provide basis and guidance for improving indoor heating effect by HAPCHB.

Accurate identification of soil thermal parameters and groundwater flow from thermal response tests

The soil heat transfer parameters constitute the key information required for designing ground source heat pump (GSHP). Due to the simplification of the common analytical models, traditional methods are difficult to achieve accurate identification of soil thermal parameters and seepage velocity simultaneously. In this work, a high-precision method to simultaneously identify soil thermal conductivity, volumetric heat capacity, and seepage velocity based on deep neural network is proposed. Through the inversed orthogonal method, the training and validation samples are obtained from a large number of thermal response tests (TRTs) on a full-scale simulation platform. The accuracy of this method was verified by comparing identification results with the true values. Meanwhile, the uncertainty of identification results under different noise conditions was quantified, and the impact of test duration was discussed. The results showed that when the maximum random noise is 0.1 °C, the identification errors of the thermal conductivity, volumetric heat capacity, and seepage velocity are only 1.14 %, −4.34 %, and −3.08 %, respectively. The identification reliability can be improved by obtaining the average value of the results under multiple tests and extending the test duration. When the test duration increased from 50 to 100 h, the uncertainty of the identified parameters reduced by 54.57 %, 48.41 %, and 65.70 %, respectively.

Evaluating influence of weather on Ascochyta blight severity in chickpea using correlation network, regression and principal component analysis

Aim: Weather parameters play a critical role in the survival and propagation of the causal pathogen Ascochyta rabiei. In the absence of vertical host resistance, the present study was designed to explore the weather-disease interrelationship for effective disease management. Methodology: Field experiments were conducted with three chickpea cultivars and three sowing times for two years. The relationship between the percent severity index (PSI) at weekly interval and observed weather data was explored using multivariate statistical techniques. Results: The correlation networks revealed that temperature and relative humidity parameters were negatively and positively associated with the blight PSI, respectively. Humid thermal ratio (HTR) significantly correlated with PSI among all three chickpea cultivars. The linear regression of PSI with weather variables exhibited a significant negative slope (β) with all thermal variables whereas a strong positive β was displayed with relative humidity and HTR. The Best subset multiple regression models further affirmed that PSI in three chickpea cultivars can be strongly predicted with models constituted with temperature, humidity and HTR. Principal component analysis showed that PC1 and PC2 explained 88.2% variability with weather variables affecting the PSI. The clustering of thermal and humidity condition parameters around the first two PCs explained their pivotal role in disease severity progress. Interpretation: The multivariate analysis revealed that air temperature, relative humidity and HTR had significant influence on periodic Ascochyta blight severity in chickpea crop. Present exploration will be vital in developing more targeted disease prediction and management strategies to secure chickpea production. Key words: Ascochyta blight, Best subset regression, Chickpea, Correlation network, Weather variables

Stability optimization of energetic particle driven modes in nuclear fusion devices: the FAR3d gyro-fluid code

The development of reduced models provide efficient methods that can be used to perform short term experimental data analysis or narrow down the parametric range of more sophisticated numerical approaches. Reduced models are derived by simplifying the physics description with the goal of retaining only the essential ingredients required to reproduce the phenomena under study. This is the role of the gyro-fluid code FAR3d, dedicated to analyze the linear and nonlinear stability of Alfvén Eigenmodes (AE), Energetic Particle Modes (EPM) and magnetic-hydrodynamic modes as pressure gradient driven mode (PGDM) and current driven modes (CDM) in nuclear fusion devices. Such analysis is valuable for improving the plasma heating efficiency and confinement; this can enhance the overall device performance. The present review is dedicated to a description of the most important contributions of the FAR3d code in the field of energetic particles (EP) and AE/EPM stability. FAR3d is used to model and characterize the AE/EPM activity measured in fusion devices as LHD, JET, DIII-D, EAST, TJ-II and Heliotron J. In addition, the computational efficiency of FAR3d facilitates performing massive parametric studies leading to the identification of optimization trends with respect to the AE/EPM stability. This can aid in identifying operational regimes where AE/EPM activity is avoided or minimized. This technique is applied to the analysis of optimized configurations with respect to the thermal plasma parameters, magnetic field configuration, external actuators and the effect of multiple EP populations. In addition, the AE/EPM saturation phase is analyzed, taking into account both steady-state phases and bursting activity observed in LHD and DIII-D devices. The nonlinear calculations provide: the induced EP transport, the generation of zonal structures as well as the energy transfer towards the thermal plasma and between different toroidal/helical families. Finally, FAR3d is used to forecast the AE/EPM stability in operational scenarios of future devices as ITER, CFETR, JT60SA and CFQS as well as possible approaches to optimization with respect to variations in the most important plasma parameters.

Thermal concentrating efficiency enhanced for multilayer circular thermal concentrators with gradient structures

The thermal concentrating efficiency of a thermal concentrator is determined by the ratio of its interior to exterior temperature gradients, serving as a crucial indicator influenced by the interaction of geometrical and thermal conductivity parameters. Finding simpler and more effective ways to improve thermal concentrating efficiency has been a key concern in this field. In our study, we present a method to enhance the concentrating efficiency of an isotropic multilayer circular thermal concentrator by introducing gradient-distributed thermal conductivities or layer thicknesses within the multilayer circular structure. Our goal is to identify the optimal structural setup parameters for achieving enhanced thermal concentrating efficiency using an optimization approach that combines stepwise refinement search with machine-learning predictions. Initial investigations explore the impacts of different gradient schemes on thermal concentration performance. The gradient distribution function with high thermal concentrating efficiency is established through the stepwise refinement search strategy and the machine-learning model. Subsequently, a detailed search process is carried out in small increments, followed by finite element simulations to validate the thermal concentrating efficiency and ascertain the optimal design parameters of the thermal concentrator. Our findings reveal that the optimally designed gradient thermal concentrator showcases an 8.56 % increase in thermal concentrating efficiency compared to a single-layer structure without gradients. Moreover, applying the gradient function to the outer and inner rings elucidates the inherent influence of the inner and outer layered ring structures on thermal concentrating efficiency. The optimization methodology, combining stepwise refinement search and machine-learning predictions, succeeds in improving the efficiency with easy, fast and efficient operation. This approach can be extended to advance the development of various other thermal metastructured devices.

Stability analysis of dual solutions for nonlinear radiative magnetohydrodynamic flow of [formula omitted] hybrid nanofluid over a nonlinearly shrinking surface

The present work explores the existence and temporal stability of dual solutions with the consequence of nonlinear thermal radiation on hybrid nanofluid flow (including Silver and Titanium dioxide nanoparticles in water) past a permeable shrinking sheet. The analysis also considers the united outcomes of suction/injection, Joule heating, viscous dissipation, and magnetohydrodynamics. Employing realistic assumptions and suitable similarity transformations, the governing nonlinear partial differential equations are formulated and altered into a nonlinear ordinary differential equations system. These equations are then solved numerically using the Lobatto IIIA technique. It is observed that dual solutions can occur within a precise range of the shrinking surface parameter. Analyzing the temporal stability of these dual solutions under small disturbances shows that the upper solution branch is stable and represents a physically realistic solution to the problem. In contrast, the lower solution branch is unstable and not physically realizable. No solution exists beyond the critical λc=−1.3915 for the shrinking parameter. The critical values of shrinking parameter λc=−1.2565,−1.3188, and −1.4161 correspond to volume fractions of hybrid nanofluid with φAg−TiO2 of 2%,4%, and 8%, respectively. No solution exists beyond this critical point. The graphical representation and quantitative explanation demonstrate how various emergent characteristics affect momentum and thermal boundary layer profiles, Nusselt number, and skin friction. The velocity and temperature profile of hybrid nanofluid can be improved by adding a small volume of nanoparticle volume fraction. Thermal boundary layer thickness is amplified by an accumulation in the shrinking parameter, power index of velocity component, thermal radiation parameter, and temperature difference ratio. Sheering stress and heat transfer coefficient improve with adding more nanoparticles in the base fluid for the first solution braches, but opposite effects are found in the second solutions. The contributions of this research are significant both theoretically, in terms of advancing the mathematical modeling of hybrid nanofluid flow with heat transfer in engineering systems, and practically, in terms of applications to engineering cooling systems.

Immersion cooling of a cylindrical battery module: An optimum configuration using CFD, NSGA-II and desirability function approach

Immersion cooling offers promising advantages for cylindrical battery modules, particularly in applications where compact design, efficient thermal management, and enhanced safety are critical factors. In this study, the geometric, thermal, and dynamic parameters of an immersion-cooled battery module with 14 NCM cylindrical cells are analyzed using CFD methods. The developed battery model is experimentally validated, establishing the constraints through numerical analysis of the impact of design parameters on response values. The design parameters are optimized using a multi-objective optimization technique. The study models the battery module with mineral oil cooling and examines the impact of each parameter on variables such as maximum battery module temperature (Tmax), pressure drop (ΔP), maximum temperature variance (ΔTmax), and battery module mass index (Im). A Design of Experiment set, created with Central Composite Design (CCD), is solved using CFD methods, and quadratic correlation equations are derived using backward regression. The regression models for Tmax, ΔTmax, ΔP, and Im show high accuracy with R2 values close to 1.0. Optimization is performed using the entropy weight-based composite desirability function approach, yielding optimum values for cell center spacing (t), coolant mass flow rate (ṁc), and coolant inlet temperature (Ti) at 20.606 mm, 1.5 kg/s, and 23 °C, respectively. The optimized design sets are validated through CFD analysis, showing a maximum deviation of 4.27 %. Reducing t boosts thermal performance but lowers hydraulic performance, while the reverse occurs for ṁc. As Ti decreases, effective cooling improves, but temperature uniformity suffers.

Thermal response of TBC systems subjected to non-uniform thermal shocks and periodic thermal load: Effect of Biot number and interface imperfection

This study analytically examines the temperature variations within thermal barrier coating (TBC) systems under diverse kinds of thermal loadings, such as concentrated/distributed convective thermal shocks and oscillating thermal loads. In this study, the TBC system comprises ceramic top coat (TC) and NiCrAlY alloy bond coat (BC). The transient behavior of the TBC system facing various kinds of non-uniform convective thermal shocks is elaborated via the dual-phase-lag (DPL) heat conduction model. The effect of imperfect bonding of the TC/BC interface on transient responses of the regions in the neighborhood of the TC/BC interface is studied by considering impermeable, partially permeable and completely permeable heat flux flows. Laplace and Fourier integral transforms are employed to derive the exact solutions of time-dependent temperature fields governing equations. The prominent effects of sudden thermal impulse and steady alternating thermal loading on the variations of temperature within the TC, BC and substrate are inspected. The analysis reveals that the kind of thermal load, loading parameters, thermal properties and thickness of ceramic TC directly affect the transient/periodic temperature fields inside the TBC constituents. Meanwhile, the interface imperfection and the Biot number of convective thermal load play an impressive role in the severity of thermal response of the TBC constituents.

Thermal energy propagation characteristics and hazard effects of hydrogen cloud explosion

Hydrogen has advantages such as high energy density and zero carbon emissions, but it poses a risk of generating explosion fireballs in the air. The gas explosion process not only involves thermal radiation from the fireball but also heat conduction and convection caused by the diffusion of high-temperature products. In this work, the thermal parameters of hydrogen cloud explosion with different equivalence ratios and gas cloud radius in an unconfined space were investigated. The results show that the flame temperature-distance curve of a hydrogen explosion exhibited a ’Z’ type. The maximum distance of flame propagation is positively correlated with the peak thermal radiation flux and cloud radius and increases first and then remains steady with the equivalence ratio. When only considering thermal convection, the minimum injury distance of flame temperature is achieved, and the thermal radiation effect can promote the flame propagation speed. Under the q-t criterion, the effective thermal radiation radius of first-level damage at a gas cloud size of 1 m was 6.11 m at φ = 1.2, which was 1.89 times that of φ = 0.6. Compared with the thermal dose criterion, the thermal flux-time criterion results in a larger thermal injury radius. The propulsion effect of hydrogen explosion products can cause the hydrogen cloud in the premixed zone to diffuse outward. The critical distance of hydrogen diffusion within the lower explosion limit was also analyzed. This study provides significant guiding implications for preventing hazards in people and buildings.

Parametric optimization and energy loss analysis of a solar thermophotonic energy converter

In the present work, the model of a solar thermophotonic energy converter (STEC) is established, of which the energy balance constraint equations at both the hot and cold sides are numerically solved to uncover the dependencies of the operating temperatures of the light emitting diode (LED) and photovoltaic (PV) cell on thermal, electrical, and structural parameters. For a given band-gap 0.36 eV of the semiconductor and a concentrated factor 20 of the concentrator, the LED’s bias voltage and the PV cell’s output voltage are optimized to achieve a local maximum efficiency 13% of the STEC. Furthermore, the conditions are optimized to attain an overall maximum efficiency of 15.94%. The distributions of energy losses are presented to reveal the underlying loss mechanisms. The results obtained in this work can provide theoretical guidance for the efficient utilization of solar energy.

Significance of tri‐hybrid nanoparticles on the dynamics of Ellis rotating nanofluid with thermal stratification

AbstractThe fluids flow containing nano size particles is essential in industrial applications, especially in nuclear cooling system and nuclear reactor to increase the energy performance. In connection to this, a trihybrid Ellis rotating nanofluid flow through a stretching surface for increasing the heat transportation is presented. By suspending three different types of nano size particles the trihybrid nanofluid is formed with distinct chemical and physical connection into base liquid. In this article, the nano size particles , and are mixed in (water). This type of mixture helps in degradation of noxious substances, cleaning environmental and many other appliances that requires the cooling effect. In addition, the linear thermal radiation is also considered. The governing equations of the flow and fluid temperature are minimized to ordinary differential equations and these equations are solved by Runge Kutta order fourth (RK45) approach. The approximate results are analyzed via graphs and the results reveal that thermal conductivity of trihybrid nano type fluid is more valuable as compared to hybrid and single nanofluid. Higher values of magnetic and rotational parameter have aggrandized the fluid temperature and opposite trend has observed for Ellis and thermal stratification parameter. Moreover, the results are compared with previous literature and found an excellent agreement.

Electron diffraction structure analysis of the amorphous polytetrafluoroethylene film

A thin amorphous film of fluoroplast (polytetrafluoroethylene) was obtained and studied by the electron diffraction structure analysis methods. The previously developed method of constructing the radial distribution function of atoms by the electron diffraction patterns from amorphous structures is applied, based on the determination of the normalization coefficient by varying the thermal parameter. The possibility of applying and necessary adaptations of this technique for the studied polytetrafluoroethylene samples are shown, taking into account its not quite usual amorphous structure due to the rigid spiral conformation of polymer chains …–CF2–…, which does not allow us to speak about the complete absence of the long-range order of the arrangement of atoms along the direction of the spiral axis. The measurements were carried out using the developed registration system on the electron diffraction camera EMR-102.

Research on Operation Characteristics of Passive Containment Heat Removal System in Typical Accident Conditions

In order to verify the feasibility of the design of the third generation of nuclear power plant independently developed in China, this study investigated the operation characteristics of the passive containment heat removal system under five working conditions using the passive containment heat removal system general performance verification facility: the design conditions, low water level conditions, low pressure conditions in the containment, extreme accidents conditions and resistance increasing conditions are analyzed, and the thermal characteristics, power requirements and thermal parameters of the containment under different operating conditions are analyzed. The results show that the heat dissipation capacity of the passive containment heat removal system exceeds the design requirements under the design conditions. Under off-design low pressure conditions, the pressure in the system is significantly affected. The decrease in the cooling water tank’s water level not only did not adversely affect the operation of the system but instead led to a significant increase in the system’s heat dissipation power. In the case of extreme accidents, the system may initially stall, but a stable natural cycle can then be established. As the system resistance coefficient increases, the heat dissipation power of the passive containment heat removal system exhibits an approximate linear decreasing trend.

Thermal radiation, Soret and Dufour effects on MHD mixed convective Maxwell hybrid nanofluid flow under porous medium: a numerical study

PurposeScientists have been conducting trials to find ways to reduce fuel consumption and enhance heat transfer rates to make heating systems more efficient and cheaper. Adding solid nanoparticles to conventional liquids may greatly improve their thermal conductivity, according to the available evidence. This study aims to examine the influence of external magnetic flux on the flow of a mixed convective Maxwell hybrid non-Newtonian nanofluid over a linearly extending porous flat plate. The investigation considers the effects of thermal radiation, Dufour and Soret.Design/methodology/approachThe mathematical model is formulated based on the fundamental assumptions of mass, energy and momentum conservation. The implicit models are epitomized by a set of interconnected nonlinear partial differential equations, which include a suitable and comparable adjustment. The numerical solution to these equations is assessed for approximate convergence by the Runge−Kutta−Fehlberg method based on the shooting technique embedded with the MATLAB software.FindingsThe findings are presented through graphical representations, offering a visual exploration of the effects of various dynamic parameters on the flow field. These parameters encompass a wide range of factors, including radiation, thermal and Brownian diffusion parameters, Eckert, Lewis and Soret numbers, magnetic parameters, Maxwell fluid parameters, Darcy numbers, thermal and solutal buoyancy factors, Dufour and Prandtl numbers. Notably, the authors observed that nanoparticles with a spherical shape exerted a significant influence on the stream function, highlighting the importance of nanoparticle geometry in fluid dynamics. Furthermore, the analysis revealed that temperature profiles of nanomaterials were notably affected by their shape factor, while concentration profiles exhibited an opposite trend, providing valuable insights into the behavior of nanofluids in porous media.Originality/valueA distinctive aspect of the research lies in its novel exploration of the impact of external magnetic flux on the flow of a mixed convective Maxwell hybrid non-Newtonian nanofluid over a linearly extending porous flat plate. By considering variables such as solar radiation, external magnetic flux, thermal and Brownian diffusion parameters and nanoparticle shape factor, the authors ventured into uncharted territory within the realm of fluid dynamics. These variables, despite their significant relevance, have not been extensively studied in previous research, thus underscoring the originality and value of the authors’ contribution to the field.

Thermal feedback in coaxial superconducting radio frequency cavities

The surface resistance of superconducting radio frequency (SRF) cavities depends on the strength of the applied rf field. This field dependence is caused by a combination of intrinsic losses and the extrinsic thermal feedback (TFB) effect. To test theories of intrinsic field dependence, the extrinsic part must be compensated for when analyzing experimental data from SRF cavity tests. Performing this compensation requires knowing thermal parameters that describe heat flow in the cavity walls. The relevant thermal parameters have been measured in the case of superfluid helium, below 2.177 K, but no detailed measurements have yet been reported for cooling of niobium surfaces in normal fluid helium baths. Because of this, the impact of TFB on the field dependence at temperatures near 4.2 K is unknown. In the present study, we report measurements of normal fluid helium boiling from niobium surfaces and its dependence on the orientation of the boiling surface and bath temperature. These measurements are used to create a finite-element model of heat transfer in cavities from TRIUMF’s coaxial test program. This tool is then used to compensate for TFB when analyzing a range of datasets from this program. Results are presented showing that TFB has a weak impact for the temperatures of 2.0 and 4.2 K, where SRF cavities are usually operated, but it is an important effect at intermediate temperatures. Published by the American Physical Society 2024

A Study on Outdoor Thermal Comfort of College Students in the Outdoor Corridors of Teaching Buildings in Hot and Humid Regions

It is important to create a favorable environment for various student activities and interactions by improving the thermal comfort of semi-outdoor spaces in teaching buildings. However, there has been limited research focusing on the thermal comfort levels of college students in these areas, such as corridors (access ways connecting different buildings outdoors). This study aims to assess the thermal comfort levels of college students in the corridors of teaching buildings in hot and humid regions. Based on field measurements and questionnaire surveys, the study evaluated the thermal comfort levels of male and female college students. The findings indicate the following: (1) air temperature and air velocity are the primary thermal environmental parameters affecting college students in corridor spaces, regardless of gender; (2) physiological equivalent temperature (PET) and Universal Thermal Climate Index (UTCI) were used as indices to evaluate the thermal environment of outdoor corridor spaces. Males and females perceive the outdoor environment as hot when PET (UTCI) values reach 33.5 (34.5) °C and 33.3 (33.5) °C, respectively. When the PET (UTCI) values reach 39.0 °C (37.5 °C) for males and 37.7 °C (38.3 °C) for females, individuals in corridor spaces will face extreme heat stress; (3) females find it more challenging than males to tolerate hot outdoor environments. The unacceptable temperatures for males and females are 31.1 °C and 31.8 °C, respectively; and (4) in hot outdoor environments, females are more susceptible than males to experiencing fatigue and negative emotions. The results of this study provide valuable insights for the future design and renovation of teaching buildings on university campuses.

LYαNNA: A deep learning field-level inference machine for the Lyman-α forest

The inference of astrophysical and cosmological properties from the Lyman-α forest conventionally relies on summary statistics of the transmission field that carry useful but limited information. We present a deep learning framework for inference from the Lyman-α forest at the field level. This framework consists of a 1D residual convolutional neural network (ResNet) that extracts spectral features and performs regression on thermal parameters of the intergalactic medium that characterize the power-law temperature-density relation. We trained this supervised machinery using a large set of mock absorption spectra from NYX hydrodynamic simulations at z = 2.2 with a range of thermal parameter combinations (labels). We employed Bayesian optimization to find an optimal set of hyperparameters for our network, and then employed a committee of 20 neural networks for increased statistical robustness of the network inference. In addition to the parameter point predictions, our machine also provides a self-consistent estimate of their covariance matrix with which we constructed a pipeline for inferring the posterior distribution of the parameters. We compared the results of our framework with the traditional summary based approach, namely the power spectrum and the probability density function (PDF) of transmission, in terms of the area of the 68% credibility regions as our figure of merit (FoM). In our study of the information content of perfect (noise- and systematics-free) Lyα forest spectral datasets, we find a significant tightening of the posterior constraints – factors of 10.92 and 3.30 in FoM over the power spectrum only and jointly with PDF, respectively – which is the consequence of recovering the relevant parts of information that are not carried by the classical summary statistics.

Impacts of fossil fuel thermophoretic convective heat transfer on climate change with variable viscosity and thermal conductivity

The main aim of the current study is to analyze the impacts of fossil fuel thermophoretic convective heat transfer on climate change with variable viscosity and thermal conductivity. Furthermore, the purpose of the proposed problem is to develop a mathematical model based on three regions: source region (in terms of rectangular coordinates), plume region (in terms of cylindrical coordinates), and atmospheric region (in terms of spherical coordinates). The fossil fuels release thermophoretic particles, such as carbon dioxide, methane, black carbon, and many others, during burning process in the source region, and then release through the plume region. These particles are then distributed into the atmosphere, where the impact of thermophoretic particles on climate change is analyzed. The modeled nonlinear partial differential equations are transformed into a dimensionless form using suitable non-dimensional scaling variables. The proposed model is solved using finite difference approach in order to analyze the impacts of fossil fuel thermophoretic particles in the atmosphere in terms of climate change. In this regard, the effect of dimensionless parameters, viscosity variation parameter γ, Schimdt number Sc, thermal conductivity variation parameter ε, coefficient of thermophoretic process k, and thermophoresis parameter Nt on the velocity, temperature, and thermophoretic concentration fields are discussed. The main novelty of current work is that three models in three regions are coupled via trans-boundaries in term of temperature differences. It is very interesting to note that the concentration of thermophoretic particles, along with temperature profile, is maximum at α=π rad and minimum at α=1.5 rad in the atmospheric region.

Chebyshev spectral Newton iterative analysis on unsteady oblique stagnation flow of Maxwell fluids over an oscillating-rotating disk with Cattaneo–Christov double diffusion

Oblique stagnation flow on a rotating disk is commonly observed in processes such as spinning coating and thin film deposition techniques. The investigation of the unsteady oblique stagnation point flow for Maxwell fluid over an oscillating-rotating disk embedded in a porous medium is meticulously conducted by employing the Darcy–Maxwell framework in conjunction with Cattaneo–Christov double diffusion model. A transformation of similarity is applied to reframe the governing equations into a system of non-dimensional coupled partial differential equations, whose numerical solutions are secured by the Chebyshev Spectral Newton Iterative Scheme. The outcomes underscore that an escalation in the Darcy parameter escalates the resistance within the porous medium, consequently leading to a reduction in velocity. Both the first-order slip and the second-order slip mitigate the fluid's interaction with the disk wall, leading to a retardation in flow velocity. Additionally, the presence of augmented thermal radiation parameters is observed to enhance heat transfer efficiency, resulting in a more homogenized temperature distribution. The two-dimensional and three-dimensional streamlines provide a precise depiction of the flow characteristics at the oblique stagnation point on the oscillating-rotating disk. These findings offer a theoretical foundation that can be instrumental for forthcoming research in analogous fields.