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The purpose of this paper is to discuss the recognizability of Cantorian stochastic automata by generalized entropy‐like qualities.

The paper gives a necessary entropy condition, valid for all sequences on the alphabet {0, 1} read by lumping and generated by a Cantorian stochastic automaton.

The paper finds that, on this basis, once can determine that a given sequence is not generated by Cantorian stochastic automata and reconstruct the automaton when the sequence is generated by a Cantorian stochastic automaton.

This paper derives a new diagnostic for Cantorian stochastic automata, which could find a direct application to biology, where there is a recent claim that the coding regions of chromosomes form Cantor sets.

The purpose of this paper is to study flow over two heat generating porous blocks situated in a cavity, and examine the effects of porous blocks geometric orientations in the cavity (configurations) and the amount of heat generation in the blocks on entropy generation rate due to heat transfer and fluid flow.

Four configurations of blocks and three heat fluxes are accommodated in the simulations. The equilibrium flow equations are used to compute the flow field. Entropy generation in the flow system due to fluid friction and heat transfer is also computed. A control volume approach is used to discretize the governing equations of flow and heat transfer. In the simulations, flow Reynolds number is kept 100 at cavity inlet and blocks' porosity is set to 0.9726.

The volumetric entropy generation rate attains high values around the blocks and configuration 4 results in reasonably low values of entropy generation rate due to heat transfer and fluid flow.

The simulations are limited to low Reynolds numbers due to practical applications. However, at high Reynolds numbers, flow separation in the cavity results in complex flow structure, which is difficult to simulate.

The thermodynamic irreversibility of the thermal system in the cavity becomes low for certain configuration of blocks in the cavity. The power loss, in this case, becomes less.

The work introduces original findings for cooling applications. When porous blocks are used for electronic cooling, the blocks configurations are very important. This is clearly demonstrated in this study.

Given a time‐series, what is the best partitioning of the state space in order to obtain reasonable values for the block entropies? The purpose of this paper is to provide a simple answer (an algorithm), although approximative, in connection with symbolic dynamics and statistical properties of 1‐d maps on the interval.

The logistic map is examined as an archetype of a Complex System with different behaviors, namely: periodicity, order‐to‐chaos period‐doubling transition, weak chaos, parametric intermittent chaos, developed chaos and fully developed chaos. For the logistic map the generating partition is known, and allows comparison with other prescriptions in the literature. The partitioning of the phase space with the easy generated bipartition induced by the mean value of a curve in the plane, gives results in good agreement (roughly up to a 20 per cent difference) with the results of the generating partition, if the trajectory of the system is in parametric intermittent chaos and in developed chaos (DC). In the case of fully developed chaos (FDC), the agreement is perfect.

The authors confirm that a statistical partitioning is almost equivalent with the exact partitioning for the logistic map.

The paper updates previous results and proposes a better understanding on the partitioning for symbolic dynamics.

One of the major challenges in the design of thermal equipment is to minimize the entropy production and enhance the thermal dissipation rate for improving energy efficiency of the devices. In several industrial applications, the structure of thermal device is cylindrical shape. In this regard, this paper aims to explore the impact of isothermal cylindrical solid block on nanofluid (Ag – H₂O) convective flow and entropy generation in a cylindrical annular chamber subjected to different thermal conditions. Furthermore, the present study also addresses the structural impact of cylindrical solid block placed at the center of annular domain.

The alternating direction implicit and successive over relaxation techniques are used in the current investigation to solve the coupled partial differential equations. Furthermore, estimation of average Nusselt number and total entropy generation involves integration and is achieved by Simpson and Trapezoidal’s rules, respectively. Mesh independence checks have been carried out to ensure the accuracy of numerical results.

Computations have been performed to analyze the simultaneous multiple influences, such as different thermal conditions, size and aspect ratio of the hot obstacle, Rayleigh number and nanoparticle shape on buoyancy-driven nanoliquid movement, heat dissipation, irreversibility distribution, cup-mixing temperature and performance evaluation criteria in an annular chamber. The computational results reveal that the nanoparticle shape and obstacle size produce conducive situation for increasing system’s thermal efficiency. Furthermore, utilization of nonspherical shaped nanoparticles enhances the heat transfer rate with minimum entropy generation in the enclosure. Also, greater performance evaluation criteria has been noticed for larger obstacle for both uniform and nonuniform heating.

The current numerical investigation can be extended to further explore the thermal performance with different positions of solid obstacle, inclination angles, by applying Lorentz force, internal heat generation and so on numerically or experimentally.

A pioneering numerical investigation on the structural influence of hot solid block on the convective nanofluid flow, energy transport and entropy production in an annular space has been analyzed. The results in the present study are novel, related to various modern industrial applications. These results could be used as a firsthand information for the design engineers to obtain highly efficient thermal systems.

The purpose of this paper is to study the influence of magnetic field on entropy generation and natural convection inside an enclosure filled with a hybrid nanofluid and having a conducting wavy solid block. Also, the effect of fluid–solid thermal conductivity ratio is investigated.

The governing equations that are formulated in the dimensionless form are discretized via finite volume method. The velocity–pressure coupling is assured by the SIMPLE algorithm. Heat transfer balance is used to verify the convergence. The validation of the numerical results was performed by comparing qualitatively and quantitatively the results with previously published investigations.

The results indicate that the magnetic field and the conductivity ratio of the wavy solid block can significantly affect the dynamic and thermal field and, consequently, the heat transfer rate and entropy generation because of heat transfer, fluid friction and magnetic force.

To the best of the authors’ knowledge, the present numerical study is the first attempt to use hybrid nanofluid for studying the entropy generation because of magnetohydrodynamic natural convective flow in a square cavity with the presence of a wavy circular conductive cylinder. Irreversibilities due to magnetic effect are taken into account. The effect of fluid–solid thermal conductivity ratio is considered.

The study aims to investigate magnetohydrodynamics thermal convection energy transference and entropy production in an open chamber saturated with ferrofluid having an isothermal solid block.

Analysis of thermal convection phenomenon was performed for an open chamber saturated with a nanofluid having an isothermal solid unit placed inside the cavity with various aspect ratios. The left border temperature is kept at T_c. An external cooled nanofluid of fixed temperature T_c penetrates into the domain from the right open border. The nanofluid circulation is Newtonian, incompressible, and laminar. The uniform magnetic field of strength B at the tilted angle of γ is applied. The finite volume technique is used to work out the non-linear equations of liquid motion and energy transport. For Rayleigh number (Ra=1e+7), numerical simulations were executed for varying the solid volume fractions of the nanofluid (ϕ = 0.01–0.04), the aspect ratios of a solid body (A_s = 0.25–4), the Hartmann number (Ha = 0–100), the magnetic influence inclination angle (γ = 0–π/2) and the non-dimensional temperature drop (Ω = 0.001–0.1) on the liquid motion, heat transference and entropy production.

Numerical outcomes are demonstrated by using isolines of temperature and stream function, profiles of mean Nusselt number and entropy generations. The results indicate that the entropy generation rate and mean Nu can be decreased with an increase in Ha. The inner solid block of A_s = 0.25 reflects the maximum heat transfer rate in comparison with other considered blocks. The addition of nano-sized particles results in a growth of energy transport and mean entropy generations.

An efficient computational technique has been developed to solve natural convection problem for an open chamber. The originality of this research is to scrutinize the convective transport and entropy production in an open domain with inner body. The outcomes would benefit scientists and engineers to become familiar with the investigation of convective energy transference and entropy generation in open chambers with inner bodies, and the way to predict the energy transference strength in the advanced engineering systems.

In this work we perform a detailed entropy analysis of some substitutive sequences using the technique of lumping. The basic novelty of the entropy analysis by lumping is that, unlike the Fourier transform or the conventional entropy analysis by gliding, it gives results that can be related to algorithmic aspects of the sequences and in particular with the important property of automaticity. All computations in this paper have been performed with TOOLS FOR SYMBOLIC DYNAMICS a Maple package developed by the authors.

This study aims to investigate a three-dimensional computational modelling of free convection of Al₂O₃ water-based nanofluid in a cylindrical cavity under heterogeneous heat fluxes that can be used as a thermal storage tank.

Effects of different heat flux boundary conditions on heat transfer and entropy generation were examined and the optimal configuration was identified. The simulation results for nanoparticle (NP) volume fractions up to 4 per cent, and Rayleigh numbers of 10⁴, 10⁵ and 10⁶ were presented.

The results showed that for low Ra (10⁴) the heat transfer and entropy generation patterns were symmetric, whereas with increasing the Rayleigh number these patterns became asymmetric and more complex. Therefore, despite the symmetric boundary conditions imposed on the periphery of the enclosure (uniform in Ɵ), it was necessary to simulate the problem as three-dimensional instead of two-dimensional. The simulation results showed that by selecting the optimal values of heat flux distribution and NP volume fraction for these systems the energy consumption can be reduced, and consequently, the energy efficiency can be ameliorated.

The results of the present study can be used for the design of energy devices such as thermal storage tanks, as both first and second laws of thermodynamics have been considered. Using the optimal design will reduce energy consumption.

This study aims to review the recent advancements in high entropy alloys (HEAs) called high entropy materials, including high entropy superalloys which are current potential alternatives to nickel superalloys for gas turbine applications. Understandings of the laser surface modification techniques of the HEA are discussed whilst future recommendations and remedies to manufacturing challenges via laser are outlined.

Materials used for high-pressure gas turbine engine applications must be able to withstand severe environmentally induced degradation, mechanical, thermal loads and general extreme conditions caused by hot corrosive gases, high-temperature oxidation and stress. Over the years, Nickel-based superalloys with elevated temperature rupture and creep resistance, excellent lifetime expectancy and solution strengthening L12 and γ´ precipitate used for turbine engine applications. However, the superalloy’s density, low creep strength, poor thermal conductivity, difficulty in machining and low fatigue resistance demands the innovation of new advanced materials.

HEAs is one of the most frequently investigated advanced materials, attributed to their configurational complexity and properties reported to exceed conventional materials. Thus, owing to their characteristic feature of the high entropy effect, several other materials have emerged to become potential solutions for several functional and structural applications in the aerospace industry. In a previous study, research contributions show that defects are associated with conventional manufacturing processes of HEAs; therefore, this study investigates new advances in the laser-based manufacturing and surface modification techniques of HEA.

The AlxCoCrCuFeNi HEA system, particularly the Al0.5CoCrCuFeNi HEA has been extensively studied, attributed to its mechanical and physical properties exceeding that of pure metals for aerospace turbine engine applications and the advances in the fabrication and surface modification processes of the alloy was outlined to show the latest developments focusing only on laser-based manufacturing processing due to its many advantages.

It is evident that high entropy materials are a potential innovative alternative to conventional superalloys for turbine engine applications via laser additive manufacturing.

Computed tomography (CT) scan can provide valuable information in the diagnosis of lung diseases. To detect the location of the cancerous lung nodules, this work uses novel deep learning methods. The majority of the early investigations used CT, magnetic resonance and mammography imaging. Using appropriate procedures, the professional doctor in this sector analyses these images to discover and diagnose the various degrees of lung cancer. All of the methods used to discover and detect cancer illnesses are time-consuming, expensive and stressful for the patients. To address all of these issues, appropriate deep learning approaches for analyzing these medical images, which included CT scan images, were utilized.

Radiologists currently employ chest CT scans to detect lung cancer at an early stage. In certain situations, radiologists' perception plays a critical role in identifying lung melanoma which is incorrectly detected. Deep learning is a new, capable and influential approach for predicting medical images. In this paper, the authors employed deep transfer learning algorithms for intelligent classification of lung nodules. Convolutional neural networks (VGG16, VGG19, MobileNet and DenseNet169) are used to constrain the input and output layers of a chest CT scan image dataset.

The collection includes normal chest CT scan pictures as well as images from two kinds of lung cancer, squamous and adenocarcinoma impacted chest CT scan images. According to the confusion matrix results, the VGG16 transfer learning technique has the highest accuracy in lung cancer classification with 91.28% accuracy, followed by VGG19 with 89.39%, MobileNet with 85.60% and DenseNet169 with 83.71% accuracy, which is analyzed using Google Collaborator.

The proposed approach using VGG16 maximizes the classification accuracy when compared to VGG19, MobileNet and DenseNet169. The results are validated by computing the confusion matrix for each network type.