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This paper aims to investigate the hydrodynamic instability properties of a mixed convection flow of nanofluid in a porous channel.

The treated single-phase nanofluid is a suspension consisting of water as the working fluid and alumina as a nanoparticle. The anisotropy of the porous medium and the effects of the inclination of the magnetic field are highlighted. The effects of viscous dissipation and thermal radiation are incorporated into the energy equation. The eigenvalue equation system resulting from the stability analysis is processed numerically by the spectral collocation method.

Analysis of the results in terms of growth rate reveals that increasing the volume fraction of nanoparticles increases the critical Reynolds number. Parameters such as the mechanical anisotropy parameter and Richardson number have a destabilizing effect. The Hartmann number, permeability parameter, magnetic field inclination, Prandtl number, wave number and thermal radiation parameter showed a stabilizing effect. The Eckert number has a negligible effect on the growth rate of the disturbances.

Linear stability analysis of Magnetohydrodynamics (MHD) mixed convection flow of a radiating nanofluid in porous channel in presence of viscous dissipation.

This paper aims to investigate the impact of combining grain-oriented electrical steel (GOES) grades on specific iron losses and the flux density distribution within a single-phase magnetic core.

This paper presents the results of finite-element method (FEM) simulations investigating the impact of mixing two different GOES grades on losses of a single-phase magnetic core. The authors used different models: a 3D model with a highly detailed geometry including both saturation and anisotropy, as well as a simplified 2D model to save computation time. The behavior of the flux distribution in the mixed magnetic core is analyzed. Finally, the results from the numerical simulations are compared with experimental results.

The specific iron losses of a mixed magnetic core exhibit a nonlinear decrease with respect to the GOES grade with the lowest losses. Analyzing the magnetic core behavior using 2D and 3D FEM shows that the rolling direction of the GOES grades plays a critical role on the nonlinearity variation of the specific losses.

The novelty of this research lies in achieving an optimum trade-off between the manufacturing cost and the core efficiency by combining conventional and high-performance GOES grade in a single-phase magnetic core.

Polymethyl methacrylate (PMMA) is a remarkable biocompatible material for bone cement and regeneration. It is also considered 3D printable but requires in-depth process–structure–properties studies. This study aims to elucidate the mechanistic effects of processing parameters and sterilization on PMMA-based implants.

The approach comprised manufacturing samples with different raster angle orientations to capitalize on the influence of the filament alignment with the loading direction. One sample set was sterilized using an autoclave, while another was kept as a reference. The samples underwent a comprehensive characterization regimen of mechanical tension, compression and flexural testing. Thermal and microscale mechanical properties were also analyzed to explore the extent of the appreciated modifications as a function of processing conditions.

Thermal and microscale mechanical properties remained almost unaltered, whereas the mesoscale mechanical behavior varied from the as-printed to the after-autoclaving specimens. Although the mechanical behavior reported a pronounced dependence on the printing orientation, sterilization had minimal effects on the properties of 3D printed PMMA structures. Nonetheless, notable changes in appearance were attributed, and heat reversed as a response to thermally driven conformational rearrangements of the molecules.

This research further deepens the viability of 3D printed PMMA for biomedical applications, contributing to the overall comprehension of the polymer and the thermal processes associated with its implementation in biomedical applications, including personalized implants.

Additive manufacturing also known as 3D printing is an evolving advanced manufacturing technology critical for the new era of complex machinery and operating systems. Manufacturing systems are increasingly faced with risk of attacks not only by traditional malicious actors such as hackers and cyber-criminals but also by some competitors and organizations engaged in corporate espionage. This paper aims to elaborate a plausible risk practice of designing and demonstrate a case study for the compromised-based malicious for polymer 3D printing system.

This study assumes conditions when a machine was compromised and evaluates the effect of post compromised attack by studying its effects on tensile dog bone specimens as the printed object. The designed algorithm removed predetermined specific number of layers from the tensile samples. The samples were visually identical in terms of external physical dimensions even after removal of the layers. Samples were examined nondestructively for density. Additionally, destructive uniaxial tensile tests were carried out on the modified samples and compared to the unmodified sample as a control for various mechanical properties. It is worth noting that the current approach was adapted for illustrating the impact of cyber altercations on properties of additively produced parts in a quantitative manner. It concurrently pointed towards the vulnerabilities of advanced manufacturing systems and a need for designing robust mitigation/defense mechanism against the cyber altercations.

Density, Young’s modulus and maximum strength steadily decreased with an increase in the number of missing layers, whereas a no clear trend was observed in the case of % elongation. Post tensile test observations of the sample cross-sections confirmed the successful removal of the layers from the samples by the designed method. As a result, the current work presented a cyber-attack model and its quantitative implications on the mechanical properties of 3D printed objects.

To the best of the authors’ knowledge, this is the original work from the team. It is currently not under consideration for publication in any other avenue. The paper provides quantitative approach of realizing impact of cyber intrusions on deteriorated performance of additively manufactured products. It also enlists important intrusion mechanisms relevant to additive manufacturing.

Stainless-steel electromagnetic shielding (EMS) fabrics are widely applied as protective materials against electromagnetic interference (EMI). However, these fabrics primarily shield electromagnetic waves through reflection, which can lead to the formation of resonance effects that severely compromise their protective capabilities and potentially cause secondary electromagnetic pollution in the external environment.

In this paper, carbon nanotube fibers are added via spacing method to replace some stainless-steel fibers to impart absorbing properties to stainless-steel EMS fabric. The shielding effectiveness (SE) of the EMS fabrics across various polarization directions is analyzed. Additionally, a spacing arrangement for the carbon nanotube fibers is designed. The EMS fabric with carbon nanotube fibers is manufactured using a semi-automatic sample loom, and its SE is tested using a small window method test box in both vertical and horizontal polarization directions.

According to the experimental data and electromagnetic theory analysis, it is determined that when the spacing between the carbon nanotube fibers is less than a specific distance, the SE of the stainless-steel EMS fabric significantly improves. The fabric exhibits stable absorbing properties within the tested frequency range, effectively addressing the issue of secondary damage that arises from relying solely on reflective shielding. Conversely, as the spacing between the carbon nanotube fibers exceeds this distance, the SE diminishes. Notably, the SE in the vertical polarization direction is substantially higher than that in the horizontal polarization direction at the same frequency.

This study provides a new path for the development of high-performance EMS fabrics with good wave-absorption characteristics and SE.

This paper aims to introduce an alternative for modeling levitation forces between NdFeB magnets and bulks of high-temperature superconductors (HTS). The presented approach should be evaluated through two different formulations and compared with experimental results.

The T-A and H-ϕ formulations are among the most efficient approaches for modeling superconducting materials. COMSOL Multiphysics was used to apply them to magnetic levitation models and predict the forces involved.The permanent magnet movement is modeled by combining moving meshes and magnetic field identity pairs in both 2D and 3D studies.

It is shown that it is possible to use the homogenization technique for the T-A formulation in 3D models combined with mixed formulation boundaries and moving meshes to simulate the whole device’s geometry.

The case studies are limited to the formulations’ implementation and a brief assessment regarding degrees of freedom. The intent is to make the simulation straightforward rather than establish a benchmark.

The H-ϕ formulation considers the HTS bulk domain as isotropic, whereas the T-A formulation homogenization approach treats it as anisotropic. The originality of the paper lies in contrasting these different modeling approaches while incorporating the external magnetic field movement by means of the Lagrangian–Eulerian method.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

This paper aims to describe a proposal for an innovative method of normal shock wave–turbulent boundary layer interaction (SBLI) and shock-induced separation control.

The concept is based on the introduction of a tangentially moving wall upstream of the shock wave and in the interaction region. The SBLI control mechanism may be implemented as a closed belt floating on an air cushion, sliding over two cylinders and forming the outer skin of the suction side of the airfoil. The presented exploratory numerical study is conducted with SPARC solver (steady 2D RANS). The effect of the moving wall is presented for the NACA 0012 airfoil operating in transonic conditions.

To assess the accuracy of obtained solutions, validation of the computational model is demonstrated against the experimental data of Harris, Ladson & Hill and Mineck & Hartwich (NASA Langley). The comparison is conducted not only for the reference (impermeable) but also for the perforated (permeable) surface NACA 0012 airfoils. Subsequent numerical analysis of SBLI control by moving wall confirms that for the selected velocity ratios, the method is able to improve the shock-upstream boundary layer and counteract flow separation, significantly increasing the airfoil aerodynamic performance.

The moving wall concept as a means of normal shock wave–turbulent boundary layer interaction and shock-induced separation control has been investigated in detail for the first time. The study quantified the necessary operational requirements of such a system and practicable aerodynamic efficiency gains and simultaneously revealed the considerable potential of this promising idea, stimulating a new direction for future investigations regarding SBLI control.

The textile industry is evolving toward nanotechnology, which provides materials with self-cleaning properties. This paper aims to provide a thorough explanation of the green synthesis and mechanism of ZnO nanoparticles, with prospective applications of zinc oxide nanoparticles (ZnO NPs) in self-cleaning textiles.

This review introduces a green mechanism for the synthesis of ZnO NPs using plant extracts, their self-cleaning properties and the mechanisms of physical, chemical and biological self-cleaning actions for textile applications.

ZnO NPs are among the several nanoparticles that are beneficial for self-cleaning textiles because of their exceptional physical and chemical properties, although review publications addressing the use of ZnO NPs in textiles for self-cleaning are uncommon. These results indicate that the plant-synthesized ZnO NPs display excellent biological, physical and chemical self-cleaning properties, the mechanism of which involves photocatalysis, surface roughness and interactions between ZnO NPs and bacterial surfaces.

Nanoformulations of plant-synthesized ZnO have been reviewed to achieve promising self-cleaning textile properties and have not been reviewed earlier.