Volume Fraction Of Inclusions Research Articles

Effective elastic behavior analysis of three-layer quasicrystal composite plates

In this paper, the effective elastic behavior of three-layer quasicrystal composite plates are forecasted. Firstly, effective properties of the first and third layers quasicrystal composite plates containing ellipsoidal inclusions are obtained according to the Mori-Tanaka model. Secondly, the three-layer composite plates effective behavior parameters are computed by employing the general matrix approach. The numerical examples reveal the influence of the inclusions geometry and volume fraction on the three-layer quasicrystal composite plates effective behavior parameters. The findings indicate that changing the elastic constants of the phason field and phonon-phason coupling field of inclusions will affect the effective behavior parameters of the three-layer quasicrystal composite plates. The increase in layers to some extent reduces the effective behavioral parameters.

Decoupling the rheological responses of a soft solid emulsion with liquid inclusions

Soft solid emulsions are liquid droplets encapsulated in a soft solid material. Typical of dispersed systems, they can combine properties from both the liquid inclusions and the soft solids. The relative importance of the two phases in the rheological response is captured through the elastocapillary number, which compares capillary forces in the liquid inclusions to the matrix rigidity. We work with solid emulsions formed of poly(ethylene glycol) droplets in a poly(dimethylsiloxane) (PDMS) continuous phase. We create three families of emulsions with varying elastocapillary numbers, and range of inclusion volume fractions from 0 to 0.5. Through oscillatory rheology we probe both the elastic response and the dissipative effects of liquid droplets. In the case of a dominant response from the continuous phase or the drops, the results can be described with Palierne’s model. However, for the intermediate elastocapillary series we show that the evolution of the storage and loss moduli decouple with dispersed phase volume fraction. We attribute the increase of loss factor with volume fraction to the high polydispersity in droplet size. We can further modulate the response of the materials by cooling to freeze the droplets. This approach allows us to compare these soft solid emulsions with theories related to solid dispersions.

Crack Initiation in Compacted Graphite Iron with Random Microstructure: Effect of Volume Fraction and Distribution of Particles.

Thanks to the distinctive morphology of graphite particles in its microstructure, compacted graphite iron (CGI) exhibits excellent thermal conductivity together with high strength and durability. CGI is extensively used in many applications, e.g., engine cylinder heads and brakes. The structural integrity of such metal-matrix materials is controlled by the generation and growth of microcracks. Although the effects of the volume fraction and morphology of graphite inclusions on the tensile response of CGI were investigated in recent years, their influence on crack initiation is still unknown. Experimental studies of crack initiation require a considerable amount of time and resources due to the highly complicated geometries of graphite inclusions scattered throughout the metallic matrix. Therefore, developing a 2D computational framework for CGI with a random microstructure capable of predicting the crack initiation and path is desirable. In this work, an integrated numerical model is developed for the analysis of the effects of volume fraction and nodularity on the mechanical properties of CGI as well as its damage and failure behaviours. Finite-element models of random microstructure are generated using an in-house Python script. The determination of spacings between a graphite inclusion and its four adjacent particles is performed with a plugin, written in Java and implemented in ImageJ. To analyse the orientation effect of inclusions, a statistical analysis is implemented for representative elements in this research. Further, Johnson-Cook damage criteria are used to predict crack initiation in the developed models. The numerical simulations are validated with conventional tensile-test data. The created models can support the understanding of the fracture behaviour of CGI under mechanical load, and the proposed approach can be utilised to design metal-matrix composites with optimised mechanical properties and performance.

FE modeling to generate composite RVEs with high volume fractions and various shapes of inclusions

This work proposes a novel multi-step dynamic FE compression method to generate Representative Volume Elements (RVEs) of composites containing a variety of inclusions. This method is actualized through a sequential and four-stage procedure: (1) Sparse and periodic inclusions exhibiting a predefined orientation distribution are generated by implementing a modified random sequential adsorption algorithm, (2) Sparse inclusions undergo biaxial compression into the region of the targeted RVE via a dynamic FE analysis, (3) Periodic inclusions are compressed into the region utilizing a dynamic FE analysis with periodic boundary conditions, and (4) Positions and orientations of the compressed inclusions are extracted and the RVE in computer-aided design format is then generated. The proposed method confers advantages from four distinct perspectives: (1) applicability to various inclusion geometries, including ellipses, lobules, polygons, kidneys and stars, (2) ability to generate periodic RVEs of composites with high inclusion volume fractions (up to 80.0% for circular inclusions), (3) simple and straightforward numerical implementation without explicitly considering inclusion intersection check and (4) capacity to predefine inclusion orientation distribution. Statistical analyses utilizing multiple spatial descriptors, i.e., inclusion orientation angle, local volume fraction, Voronoi cell area, nearest-neighbor distance and orientation, second order intensity function, radial distribution function and two-point probability function, confirm randomness of inclusion distribution in the generated RVEs. The elastic properties and damage behaviors of composites via the FE homogenization method are predicted based on the generated RVEs and are compared with those of available experimental data, the literature and the mean-field homogenization models to demonstrate effectiveness of the proposed multi-step dynamic FE compression method.

Advanced design and optimization of tailored refining fluxes for the purification of Mg–Li alloys

This study systematically investigates the influence of integrating KCl into the refining flux on the purification efficiency of Mg–Li alloy. The findings reveal that an optimal purification effect is achieved with a 50 % addition of KCl to the refining flux, resulting in a remarkable 56 % reduction in volume fraction of inclusions to 0.17 % and an 80 % improvement in elongation to 29.1 %. The developed novel quaternary refining flux is composed of KCl + LiCl + LiF + CaF2 (3:3:1:2, wt.%). Based on thermodynamic calculation and analysis, the purification mechanism is elucidated, demonstrating that KCl enhances purification efficiency by reducing flux and melt viscosity, improving wettability, increasing contact area, and facilitating flux adsorption on inclusions. Excessive KCl addition hinders purification by decreasing flux density, slowing settling velocity, and affecting the purification process. The quaternary flux, applying to industrial Mg–Li alloy scrap, demonstrates outstanding purification performance with a 73 % reduction in inclusion volume fraction to 0.33 % and a remarkable 584 % increase in elongation to 17.1 %. The development and application of a novel Mg–Li alloy flux are of significant importance for promoting the industrial development of Mg–Li alloys.

SEM Image Processing Assisted by Deep Learning to Quantify Mesoporous γ-Alumina Spatial Heterogeneity and Its Predicted Impact on Mass Transfer.

The pore network architecture of porous heterogeneous catalyst supports has a significant effect on the kinetics of mass transfer occurring within them. Therefore, characterizing and understanding structure-transport relationships is essential to guide new designs of heterogeneous catalysts with higher activity and selectivity and superior resistance to deactivation. This study combines classical characterization via N2 adsorption and desorption and mercury porosimetry with advanced scanning electron microscopy (SEM) imaging and processing approaches to quantify the spatial heterogeneity of γ-alumina (γ-Al2O3), a catalyst support of great industrial relevance. Based on this, a model is proposed for the spatial organization of γ-Al2O3, containing alumina inclusions of different porosities with respect to the alumina matrix. Using original, advanced SEM image analysis techniques, including deep learning semantic segmentation and porosity measurement under gray-level calibration, the inclusion volume fraction and interphase porosity difference were identified and quantified as the key parameters that served as input for effective tortuosity factor predictions using effective medium theory (EMT)-based models. For the studied aluminas, spatial porosity heterogeneity impact on the effective tortuosity factor was found to be negligible, yet it was proven to become significant for an inclusion content of at least 30% and an interphase porosity difference of over 20%. The proposed methodology based on machine-learning-supported image analysis, in conjunction with other analytical techniques, is a general platform that should have a broader impact on porous materials characterization.

Core Optimization for Extending the Graphite Irradiation Lifespan in a Small Modular Thorium-Based Molten Salt Reactor

The lifespan of core graphite under neutron irradiation in a commercial molten salt reactor (MSR) has an important influence on its economy. Flattening the fast neutron flux (≥0.05 MeV) distribution in the core is the main method to extend the graphite irradiation lifespan. In this paper, the effects of the key parameters of MSRs on fast neutron flux distribution, including volume fraction (VF) of fuel salt, pitch of hexagonal fuel assembly, core zoning, and layout of control rod assemblies, were studied. The fast neutron flux distribution in a regular hexagon fuel assembly was first analyzed by varying VF and pitch. It was demonstrated that changing VF is more effective in reducing the fast neutron flux in both global and local graphite blocks. Flattening the fast neutron flux distribution of a commercial MSR core was then carried out by zoning the core into two regions under different VFs. Considering both the fast neutron flux distribution and burnup depth, an optimized core was obtained. The fast neutron flux distribution of the optimized core was further flattened by the rational arrangement of control rod channels. The calculation results show that the final optimized core could reduce the maximum fast neutron flux of the graphite blocks by about 30% and result in a more negative temperature reactivity coefficient, while slightly decreasing the burnup and maintaining a fully acceptable core temperature distribution.

CFD modeling of a triple‐walled direct absorption evacuated tube solar collector based on hybrid nanofluid/microencapsulated PCM

AbstractNowadays, direct absorption solar collectors are a new concept of solar collectors which have attracted special attention. The type of heat transfer fluid (HTF) has a significant influence on the efficiency of this kind of collector. Therefore, in this study, a wide range of working fluids including mono nanofluid ( and CuO), binary nanofluid, and especially the incorporation of a new hybrid combination of nanofluid and microencapsulated phase change material (MPCM), are used as the working fluids of a triple‐walled direct absorption evacuated tube solar collector. The computational fluid dynamics (CFD) method is used for simulating the collector and investigating the effect of different parameters including volume fraction, base fluid, mass flow rate, and type of absorber tube structure (double‐ and triple‐walled) on collector thermal performance. Results show that binary nanofluids of 0.06% /0.002% CuO/water and 0.06% /0.002% CuO/ethylene glycol (EG) have the largest working fluid temperature differentials equal to 48.31 and 66.5 K, respectively. It was inferred that, at the mass flow rate of 2.7 , the efficiency is obtained to be 60.29% employing binary/EG nanofluid, which is 8.68% and 15.31% higher than CuO/EG and /EG nanofluids, respectively. Inserting the hybrid CuO nanofluid/MPCM leads to an improvement of 1.14% and 1.22% in the efficiency of triple‐ and double‐walled collectors, respectively, with respect to the individual usage of the nanofluid. The thermal efficiency of the double‐walled structure is higher than triple‐walled considering all HTFs.

The effect of property contrast in two-component piezoelectric composites

A Mori - Tanaka model of piezoelectric composites is used to study the effect of property contrast between the components of a two-component composite. The composite comprises a piezoelectric matrix and piezoelectric inclusions whose property values are scaled from those of the matrix. The scaling method allows a wide range of material combinations to be approximated without using explicit properties of specific materials. Additionally, the aspect ratio and volume fraction of inclusions is varied to seek optimum values of the piezoelectric coefficients in the composite. It was found that scaling the properties in the electroelastic moduli reveals significant results for the piezoelectric performance coefficients dhgh, κ33, g33 and kt. By varying the material scaling factors alongside the inclusion aspect ratio it is demonstrated that giant enhancements of the transducer figure of merit dhgh could potentially be achieved through composite design. This approach identifies some novel opportunities for optimised piezoelectric composites.

Free vibration analysis of graphene origami-reinforced nano cylindrical shell

Vibrational behavior of a shear deformable cylindrical shell is studied in this article based on Hamilton’s principle. The shell is manufactured by a Copper (Cu) core reinforced with graphene origami auxetic metamaterial and subjected to mechanical and thermal loads. The constitutive relations are developed based on the shear deformable model where the effective modulus of elasticity, Poisson’s ratio, and density are evaluated using micromechanical models including volume fraction and folding degree of graphene origami auxetic metamaterial, geometric characteristics of graphene, material properties of matrix, and reinforcement and local temperature. The natural frequencies are obtained based on Navier’s and Galerkin’s approaches for simply supported, clamped-simply, and clamped-clamped boundary conditions. The formulation, solution procedure, and numerical results are confirmed through comparison with the available results of the literature. The complete numerical results are presented in terms of volume fraction and folding degree of graphene origami auxetic metamaterial, thermal loading, and various types of boundary conditions.

Measured and simulated mechanical properties of additively manufactured matrix-inclusion multimaterials fabricated by material jetting

Modern additive manufacturing enables the simultaneous processing of different materials during the printing process. While multimaterial 3D printing allows greater freedom in part design, the prediction of the mix-material properties becomes challenging. One type of multimaterials are matrix-inclusion composites, where one material contains inclusions of another material. Aim of this study was to develop a method to predict the uniaxial Young’s modulus and Poisson’s ratio of material jetted matrix-inclusion composites by a combination of simulations and experimental data.Fifty samples from commercially available materials in their pure and matrix-inclusion mixed forms, with cubic inclusions, have been fabricated using material jetting and mechanically characterized by uniaxial tensile tests. Multiple simulation approaches have been assessed and compared to the measurement results in order to find and validate a method to predict the multimaterials’ properties. Optical coherence tomography and microscopy was used to characterize the size and structure of the multimaterials, compared to the design.The materials exhibited Young’s moduli in the range of 1.4 GPa to 2.5 GPa. The multimaterial mixtures were never as stiff as the weighted volume average of the primary materials (up to 33.9%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$33.9\\%$$\\end{document} softer for 45% RGD8530-DM inclusions in VeroClear matrix). Experimental data could be predicted by finite element simulations by considering a non-ideal contact stiffness between matrix and inclusion (FA=2.2TNm3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$F_A=2.2\\frac{TN}{m^3}$$\\end{document} for RGD8530-DM, FA=4.8TNm3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$F_A=4.8\\frac{TN}{m^3}$$\\end{document} for RGD8430-DM), and geometries of the printed inclusions that deviated from the design (rounded edge radii of r=220μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$r=220\\,\\upmu$$\\end{document}m). Not considering this would lead to a difference of the estimation result of up to 612\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$612\\,$$\\end{document}MPa (44%), simulating an inclusion volume fraction of 45% RGD8530-DM.Prediction of matrix-inclusion composites fabricated by multimaterial jetting printing, is possible, however, requires a priori knowledge or additional measurements to characterize non-ideal contact stiffness between the components and effective printed geometries, precluding therefore a simple multimaterial modelling.

Static analysis of FGM porous cooling plates with cutouts: a multilayered approach

This study presents a comprehensive investigation into the static analysis of porous functionally graded material cooling plates with cutouts, employing a sophisticated multilayered modelling approach. The focus lies on understanding the nuanced effects of critical parameters, including volume fraction index, thickness ratio, porosity distribution, and porosity index, on the bending responses of shear-deformable porous FGM plates with cutouts. The research encompasses a diverse range of boundary conditions, both conventional and unconventional, shedding light on the collective influence of these variables on the bending response of the FGM plates featuring cutouts. In the instance of this porous FGM plate, the model integrates effective material properties obtained using a power-law distribution, which is then applied in a modified rule of mixture. The multilayered approach enhances the precision of the static analysis, providing a robust framework for exploring the mechanical behavior of porous FGM cooling plates in practical scenarios.

NUMERICAL SIMULATION OF HEAT TRANSFER IN A SQUARE CAVITY FILLED WITH HYBRID NANOFLUID

This study uses numerical simulations to investigate the characteristics of laminar natural convection in a square cavity filled with a mixed nanofluid containing Ag and Ag-TiO<sub>2</sub> solid spherical nanoparticles. The cavity contains one heat source and one heat sink, and the cavity walls are adiabatic. The fluid is a water-based hybrid nanofluid. The temperature in the cavity is randomized using a random function. The main parameters, including volume fraction of nanoparticles, temperature type, and type of hybrid nanofluid, are varied and analyzed using the finite volume method. The numerical results are compared with previous studies, and a good agreement is observed. The obtained results show that the addition of nanoparticles significantly enhanced the heat transfer in the cavity (φ = 0.1%). In addition, the larger the Rayleigh number, the more obvious the influence of temperature type. Also, the average Nusselt number increases as the volume fraction increases, and the best results are obtained from the (Ag-TiO<sub>2</sub>)/water hybrid nanofluid.

Intolerance of Ruddlesden-Popper La2NiO4±δ Structure to a-Site Cation Deficiency

Mixed ionic-electronic conductors derived from Ruddlesden-Popper Ln2NiO4+δ (Ln = La, Pr, Nd) attract significant attention as oxygen electrode materials for solid oxide fuel and electrolysis cells. However, literature data on the impact of A-site deficiency on the phase relationships and functional properties of Ln2NiO4+δ-based phases are contradictory. While some works report an accommodation of A-site vacancies up to x = 0.15 in La2-x NiO4±δ, others indicate difficulties in the synthesis of single-phase La2-x NiO4+δ even for low x values. The present work explores the impact of the nominal A-site deficiency on the phase composition and electrical transport properties of La2-x NiO4±δ ceramics.Ceramics with the nominal composition La2-x NiO4±δ (x = 0, 0.02, 0.05, 0.10) were synthesized by the glycine-nitrate technique and sintered at 1350-1450°C. While XRD analysis suggested the formation of single-phase materials with orthorhombic K2NiF4-type structure, the lattice parameters remained independent of composition within the experimental uncertainty. Neutron diffraction studies of x = 0 and 0.05 samples revealed that the lattice parameters, La:Ni atomic ratio (2:1) and oxygen sites occupancy remain identical for both samples, while the presence of impurity NiO phase (0.4 wt.%) was detected for La1.95NiO4±δ. SEM/EDS inspection of ceramic samples confirmed the presence of nickel-rich inclusions for x ≥ 0.02, which could not be eliminated by increasing the temperature and time of sintering. The volume fraction of inclusions increased with x. The experimental observations are supported by the atomistic simulations showing that the coexistence of cation-stoichiometric La2NiO4+δ with nickel-rich La4Ni3O10 or NiO is more favorable compared to cation-deficient La1.95NiO4±δ. Molecular dynamics simulations of La1.95NiO4±δ lattice demonstrated that the introduction of La vacancies leads formation of instability zone in the rock-salt-type layer and destabilization of the crystal lattice. The intolerance of La2NiO4+δ lattice to A-site vacancies and coexistence of La2NiO4+δ with traces of Ni-rich secondary phase in the samples with the nominal composition La2-x NiO4±δ results in an insignificant variation of electrical transport properties with x. Acknowledgements This work was developed within the scope of the project CARBOSTEAM (POCI-01-0145-FEDER-032295) funded by FEDER through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) and by national funds through FCT/MCTES, and the project CICECO-Aveiro Institute of Materials (UIDB/50011/2020, UIDP/50011/2020 & LA/P/0006/2020) financed by national funds through the FCT/MCTES (PIDDAC). A.B. acknowledges the PhD scholarship by the FCT (grant SFRH/BD/150704/2020). This work was partially supported by the National Science Centre, Poland, grant UMO-2020/37/B/ST8/02097.

FEATURES OF THE CONSTRUCTION OF THE STIFFNESS MATRIX OF THE SPATIAL HEXAGONAL FINITE ELEMENT FOR COMPOSITE MATERIAL WITH DISCRETE INCLUSIONS BASED ON THE MOMENT SCHEME

An approach to numerical modeling of the stress-strain state of composite structures with discrete inclusions is presented in the paper. The finite element method is used as the main method, namely its modification – the moment finite-element scheme. The moment scheme, in contrast to the classic scheme of finite elements, allows to avoid such negative properties as not taking in consideration the rigid rotation of the finite element and “false” shear. If both the material of the matrix and the material of the reinforcing inclusions are weakly compressible, then problems arise due to the fact that some elastic constants approach very large values. The Taylor series expansion of the components of the displacement vector, the components of the strain tensor, and the volume change function is used in order to eliminate the mentioned shortcomings, after that, according to the moment scheme, certain sums are removed from these expansions. Homogenization of the material with lamellar inclusions, a small proportion of spherical inclusions, and a large proportion of spherical inclusions is used for modeling the elastic properties of the composite. The chaotic nature of the location of inclusions after homogenization makes it possible to present a non-homogeneous composite material as a homogeneous quasi-isotropic one. The described approaches are used in the construction of the stiffness matrix of the spatial hexagonal finite element. The obtained expressions for the stiffness matrix are done in the software package for calculating structures from composite materials. The calculation of a thick-walled pipe under the action of internal pressure from a composite material with lamellar inclusions, a small proportion of spherical inclusions, and a large proportion of spherical inclusions was carried out using the software package. For different volume fractions of discrete inclusions, the numerical convergence of the results with different finite element meshes has been investigated, which shows great congruence with analytical solutions.

Assessing PAHs-based soot inception models in various laminar non-premixed flame configurations

Accurate soot modeling is challenging due to the complex underlying physical and chemical processes. To improve the fidelity of the soot prediction in inverse coflow flame configurations, an empirical reactive soot inception model with radical involvement was developed in our previous work [Guo et al. Combust Flame 254 (2023) 112,853]. In this study, the model is further assessed by comparing the predictions of polycyclic aromatic hydrocarbons (PAHs) and soot parameters, including volume fraction, number density, and particle size, with measurements in various laminar diffusion flame configurations. These configurations encompass counterflow diffusion flames (CDF), normal coflow diffusion flames (NDF), and inverse coflow diffusion flames (IDF). The empirical reactive inception model is also compared to the reported irreversible and reversible inception models. The results show that the empirical reactive inception model with radical involvement most accurately capture axial soot behavior in IDF configuration, while irreversible and reversible models predict a sustained increase in soot mass, inconsistent with measurements. In CDF configurations, the empirical reactive model and the reported reversible model have better performance than the irreversible inception model, regarding the predictions of spatial distributions of soot and PAHs. Moreover, in NDF configuration, the soot peaks predicted by the reactive and reversible models are in reasonable agreement with measurements within a factor of 2–3. For the soot spatial distribution in NDF, the difference in the predictions is mainly reflected in the flame wings, which is caused by the temperature dependences of the inception rate provided by the different models.

An RBF-based artificial neural network for prediction of dynamic viscosity of MgO/SAE 5W30 oil hybrid nano-lubricant to obtain the best performance of energy systems

Technological progress and complications in microfluidics usage have led researchers to use nanomaterials in different scientific fields. The properties and characteristics of hybrid Nanofluids are more enhanced compared to nanofluids based on single nanoparticles and conventional liquid. Recently, modeling methods have replaced most common statistical methods. Due to the high accuracy of the response and generalizability in various conditions, artificial neural networks (ANNs) to estimate nanofluids’ viscosity and thermal conductivity have become common. Dynamic viscosity (μ) (estimation analyzes one of the key factors in determining the hydrodynamic behavior of nanofluids. In this manuscript, an RBF-ANN is used to simulate the input-output relation of dynamic viscosity of the MgO- SAE 5W30 Oil hybrid nanofluid versus three important parameters, including volume fraction of nanoparticles, temperature, and shear rate. The results show that for this nanofluid, by increasing temperature and shear rate, the dynamic viscosity is decreased. In contrast, the volume fraction of nanoparticles directly affects the output, although this consequence can be neglected. By increasing the temperature from 5° to 55°C, the dynamic viscosity would decrease. Also, changing the shear rate from 50 to 1000 rpm decreases the dynamic viscosity from 400 cP to 25 cP. It is worth mentioning that the obtained trends and deviation of dynamic viscosity for MgO-SAE 5W30 Oil hybrid nanofluid versus temperature, the volume fraction of nanoparticles, and shear rate can be used by the academic community as well as an industrial section to obtain the best performance of energy systems based on this nanofluid.

Mathematical micro–macro modeling of fully coupled nonlinear magneto-elastic reinforced composites

In this paper, integral equation formulations and field-dependent micromechanical modeling of global nonlinear magneto-mechanical behavior of magneto-elastic composites under high strain and magnetic field are elaborated. The modeling is obtained based on an extension of micro–macro transition inclusion problem to nonlinear behavior using field-dependent and highly nonlinear localization tensors. A methodological procedure is elaborated based on newly introduced strain and magnetic field-dependent Green tensors, strain and magnetic field-dependent integral equations linked to tensors of Eshelby and micromechanical approaches. The field-dependent global moduli are predicted based on the Mori–Tanaka approach and self-consistent method. Iterative incremental schemes based on the Newton–Raphson and fixed-point algorithms are examined and established precise semi-analytic equations of the effective magneto-elastic properties of composites that are dependent on the magnetic-strain field for different types of inclusions. A numerical code is elaborated for numerical predictions and the obtained field-dependent effective magneto-elastic coefficients are obtained and presented for various volume fractions of inclusion, types and shapes of the reinforced nonlinear composites.

DISTRIBUTION OF ELECTRIC FIELDS ON THE SURFACE OF INCLUSIONS IN MATRIX COMPOSITE

Expressions are obtained for operators of concentration of electric field strength and displacement on the surface of inclusions in matrix composite depending on shape and volume fraction of inclusions in material. These operators relate the fields on the inclusion surface on the matrix side with the average values of the electric field strength and displacement in the composite sample.

Infection burden and its association with neurite orientation dispersion and density imaging markers in the UK Biobank

BackgroundInfection burden (IB), although linked to neurodegeneration, including Alzheimer’s Disease (AD), has not been examined against neurite orientation, dispersion, and density imaging (NODDI) measures. MethodsAmong 38,803 UK Biobank adults (Age:40–70 years), we tested associations of total IB (IBtotal, 47.5 %) and hospital-treated IB (IBhosp, 9.7 %) with NODDI measures (5–15 years later), including volume fraction of Gaussian isotropic diffusion (ISOVF), intra-cellular volume fraction (ICVF) and orientation dispersion (OD) indices, using multiple linear regression models. ResultsTotal and hospital-treated infection burdens (IBtotal and IBhosp) were associated with increased ISOVF, indicating increased free-water component. IBtotal was positively associated with OD, indicating that at higher IBtotal there was greater fanning of neurites. This was more evident in the lower cardiovascular health group. IBhosp was associated with higher OD, and lower ICVF at higher AD polygenic risk. Together, these findings indicate that both total and hospital-treated infections have effects on NODDI outcomes in the direction of poor brain health. These effects were largely homogeneous across cardiovascular health and AD polygenic risk groups, with some effects shown to be stronger at poor cardiovascular health and/or higher AD risk. ConclusionsTotal and hospital-treated infections were associated with poorer white matter microstructure (higher ISOVF or OD or lower ICVF), with some heterogeneity across cardiovascular health and AD risk. Longitudinal studies with multiple repeats on neuroimaging markers in comparable samples are needed.