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The presence of air in the water flow over the hydrofoil is investigated. The examined hydrofoil is ClarkY 11.7% with an angle of attack of 8 deg. The flow simulations are performed with the assumption of different models. The Singhal cavitation model and the models which resolve the non-condensable gas including 2phases and 3phases are implemented in the numerical model. The calculations are performed with the uRANS model with assumption of the constant temperature of the mixture. The two-phase flow is simulated with a mixture model. The dynamics and structures of cavities are compared with literature data and experimental results.

The cavitation regime can be observed in some working conditions of turbomachines. The phase transition, which appears on the blades, is the source of high dynamic forces, noise and also can lead to the intensive erosion of the blade surfaces. The need to control this process and to prevent or reduce the undesirable effects can be fulfilled by the application of non-condensable gases to the liquid.

The results show that the Singhal cavitation model predicts the cavity structure and related characteristics differently with 2phases and 3phases models at low cavitation number where the cavitating flow is highly dynamic. On the other hand, the impact of dissolved air on the cloud structure and dynamic characteristic of cavitating flow is gently observable.

The originality of this paper is the evaluation of different numerical cavitation models for the prediction of dynamic characteristics of cavitating flow in the presence of air.

The purpose of this paper is to present a novel model for predicting the effective viscosity of nanofluids. At present, no unified model exists for the same.

The present effective viscosity model draws upon the regression analysis of carefully selected published papers covering experimental, numerical and theoretical findings.

Unlike some other models, this one is reliable and has a good level of accuracy. This model has been assessed in a numerical investigation using a 3D horizontal pipe, and the results are presented.

This is a new model for predicting the effective viscosity of nanofluids. The proposed model has been tested in a 3D horizontal pipe, and the predicted results for viscosity and Nusselt number show good agreement with the available data.

Microstructure void volume fraction is taken into account in finite element models developed for large strain elastoplastic problems. Void nucleation rate is related to matrix effective strain rate, void growth to material strain rate and associated elastoplastic potential available for porous material, void coalescence to matrix effective strain rate. The related radial return algorithm is described. Three types of computations are proposed: first, axisymmetric Q4 element traction are given as validation example; second, collar cylinder compression are computed as reference example; third, bulk forming are analysed as large strain specific example. Void volume fraction and hydrostatic stress are mainly discussed according to microvoids nucleation, growth and coalescence. Finally, the main interests of those computations are enhanced.

The purpose of this paper is to expand the theoretical meaning and application of the separate components of the interaction coefficient as obtained from the generalized viscosity model.

Both theoretical and experimental analysis have been utilized to better understand the meaning of the separate components of the interaction coefficient obtained from the generalized viscosity model. Analysis of the experimental data of Schaller and Humphrey has been used to successfully isolate the separate components of the interaction coefficient.

The relative unhindered volume is the volume outside the sphere of influence of a particle that is responsible for the viscosity characteristics of a coating. This is the volume available for particles to move in the suspension and still contribute to the viscosity. The smaller the relative unhindered volume the higher the viscosity. As the interaction coefficient, σ, increases the particles increase their interaction with each other and the relative unhindered volume decreases. Using the data of Schaller and Humphrey, it was found that the interaction coefficient agreed best with the theoretical expectation relative to particle size when the ionic strength was low. At high levels of ionic strength, the solvent‐particle component of the interaction coefficient was dominant and the influence of particle size on the interaction coefficient was minimal.

Only one set of experimental data was successfully utilized for illustrative purposes in this study but the resulting analysis has implicated a broad range of practical applications. In addition, the general theoretical concepts elucidated relative to the interaction coefficient should still be applicable independent of the experimental results.

The analysis presented in this paper provides several practical guidelines to separate and control the charge component of pigments in a suspension from their size component using the interaction coefficient as described in this study. Consequently, the results of this study should provide several new practical approaches to use when attempting to control the viscosity of suspensions for a broad range of practical applications and for a broad range of suspension types including coatings.

This is the first time that the theoretical statistical character of the interaction coefficient as indicated in the generalized viscosity model has been specifically elucidated. In addition, the relatively simple experimental separation of the interaction coefficient into its size and electrical components has been shown to be widely applicable in this paper.

Propagation of planar (i.e. one directional), longitudinal (i.e. uniaxial strain), steady (i.e. time‐invariant) structured shock waves within metal matrix composites (MMCs) is studied computationally. Waves of this type are typically generated during blast‐wave loading or ballistic impact and play a major role in the way blast/ballistic impact loads are introduced in, and applied to, a target structure. Hence, the knowledge of the basic physics of propagation of these waves is critical for designing structures with superior blast and impact protection capabilities. The purpose of this paper is to help advance the use of computational engineering analyses and simulations in the areas of design and application of the MMC protective structures.

To derive the overall response of the composite material to shock type loading, a dynamic‐mixture model is employed. Within this model, the known constitutive responses of the constituent materials are combined using the appropriate mixture rules. These mixture rules are of a dynamic character since they depend on the current state of the composite material and cannot be applied prior to the beginning of the analysis.

The approach is applied to a prototypical MMC consisting of an aluminum matrix and SiC particulates. Both the intermediate‐to‐strong shock regime (in which the contribution of stress deviators to the stress field can be ignored) and the weak shock regime (in which stress deviators provide a significant contribution to the stress field) are investigated. Finally, the computational results are compared with their experimental counterparts available in the open literature in order to validate the computational procedure employed.

Prediction of the spallation‐type failure in a metal‐matrix composite material (modeled using the dynamic‐mixture model) has not been done previously.

This paper aims to numerically examine the mixed convection of SiO₂-water nanofluid flow in a three-dimensional (3D) cubic cavity with a conductive partition considering various shapes of the particles (spherical, cylindrical, blade, brick). The purpose is to analyze the effects of various pertinent parameters such as Richardson number (between 0.1 and 10), Hartmann number (between 0 and 10), solid nanoparticle volume fraction (between 0 and 0.04), particle shape (spherical, cylindrical, blade, brick) and different heights and lengths of the conductive partition on the fluid flow and heat transfer characteristics.

The numerical simulation was performed by using Galerkin-weighted residual finite element method for various values of Richardson number, Hartmann number, solid nanoparticle volume fraction, particle shape (spherical, cylindrical, blade, brick) and different heights and lengths of the conductive partition. Two models for the average Nusselt number were proposed for nanofluids with spherical and cylindrical particle by using multi-layer feed-forward neural networks.

It was observed that the average Nusselt number reduces for higher values of Richardson number and Hartmann number, while enhances for higher values of nanoparticle volume fraction. Among various types of particle shapes, blade ones perform the worst and cylindrical ones perform the best in terms of heat transfer enhancement, but this is not significant which is less than 3 per cent. The average Nusselt number deteriorates by about 6.53per cent for nanofluid at the highest volume fraction of spherical particle shapes, but it is 11.75per cent for the base fluid when Hartmann number is increased from 0 to 10. Conductive partition geometrical parameters (length and height) do not contribute to much to heat transfer process for the 3D cavity, except for the case when height of the partition reaches 0.8 times the height of the cubic cavity, the average Nusselt number value reduces by about 25per cent both for base fluid and for nanofluid when compared to case with cavity height which is 0.2 times the height of the cubic cavity.

Based on the literature survey, a 3D configuration for MHD mixed convection of nanofluid flow in a cavity with a conductive partition considering the effects of various particle shapes has never been studied in the literature. This study is a first attempt to use a conductive partition with nanofluid of various particle shapes to affect the fluid flow and heat transfer characteristics in a 3D cubic cavity under the influence of magnetic field. Partial or all findings of this study could be used for the design and optimization of realistic 3D thermal configurations that are encountered in practice and some of the applications were already mentioned above. In this study, thermal performance of the system was obtained in terms of average heat transfer coefficient along the hot surface, and it is modeled with multi-layer feed-forward neural networks.

The purpose of this paper is to investigate the convective heat transfer of magnetic nanofluid (MNF) inside a square enclosure under uniform magnetic fields considering nonlinearity of magnetic field-dependent thermal conductivity.

The properties of the MNF (Fe₃O₄+kerosene) were described by polynomial functions of magnetic field-dependent thermal conductivity. The effect of the transverse magnetic field (0 < H < 10⁵), Hartmann Number (0 < Ha < 60), Rayleigh number (10 <Ra <10⁵) and the solid volume fraction (0 < φ < 4.7%) on the heat transfer performance inside the enclosed space was examined. Continuity, momentum and energy equations were solved using the finite element method.

The results show that the Nusselt number increases when the Rayleigh number increases. In contrast, the convective heat transfer rate decreases when the Hartmann number increases due to the strong magnetic field which suppresses the buoyancy force. Also, a significant improvement in the heat transfer rate is observed when the magnetic field is applied and φ = 4.7% (I = 11.90%, I = 16.73%, I = 10.07% and I = 12.70%).

The present numerical study was carried out for a steady, laminar and two-dimensional flow inside the square enclosure. Also, properties of the MNF are assumed to be constant (except thermal conductivity) under magnetic field.

The results can be used in thermal storage and cooling of electronic devices such as lithium-ion batteries during charging and discharging processes.

The accuracy of results and heat transfer enhancement having magnetic field-field-dependent thermal conductivity are noticeable. The results can be used for different applications to improve the heat transfer rate and enhance the efficiency of a system.

The purpose of this paper is to describe a procedure to simulate impact-driven liquid jets by computational fluid dynamics (CFD). The proposed CFD model is used to investigate nozzle flow behavior under ultra-high injection pressure and jet velocities generated by the impact driven method (IDM).

A CFD technique was employed to simulate the jet generation process. The injection process was simulated by using a two-phase flow mixture model, while the projectile motion was modeled the moving mesh technique. CFD results were compared with experimental results from jets generated by the IDM.

The paper provides a procedure to simulate impact-driven liquid jets by CFD. The validation shows reasonable agreement to previous experimental results. The pressure fluctuations inside the nozzle cavity strongly affect the liquid jet formation. The average jet velocity and the injection pressure depends mainly on the impact momentum and the volume of liquid in the nozzle, while the nozzle flow behavior (pressure fluctuation) depends mainly on the liquid volume and the impact velocity.

Results may slightly deviate from the actual phenomena due to two assumptions which are the liquid compressibility depends only on the rate of change of pressure respected to the liquid volume and the super cavitation process in the generation process is not taken into account.

Results from this study will be useful for further designs of the nozzle and impact conditions for applications of jet cutting, jet penetration, needle free injection, or any related areas.

This study presents the first success of employing a commercial code with additional user defined function to calculate the complex phenomena in the nozzle flow and jet injection generated by the IDM.

The purpose of this paper is to develop a general mathematical model for the evaluation of the theoretical flexural responses of the functionally graded carbon nanotube-reinforced composite doubly curved shell panel using higher-order shear deformation theory with thermal load. It is well-known that functionally graded materials are a multidimensional problem, and the present numerical model is also capable of solving the flexural behaviour of different shell panel made up of carbon nanotube-reinforced composite with adequate accuracy in the absence of experimentation.

In this current paper, the responses of the single-walled carbon nanotube-reinforced composite panel is computed numerically using the proposed generalised higher-order mathematical model through a homemade computer code developed in MATLAB. The desired flexural responses are computed numerically using the variational method.

The validity and the convergence behaviour of the present higher-order model indicate the necessity for the analysis of multidimensional structure under the combined loading condition. The effect of various design parameters on the flexural behaviour of functionally graded carbon nanotube doubly curved shell panel are examined to highlight the applicability of the presently proposed higher-order model under thermal environment.

In this paper, for the first time, the static behaviour of functionally graded carbon nanotube-reinforced composite doubly curved shell panel is analysed using higher-order shear deformation theory. The properties of carbon nanotube and the matrix material are considered to be temperature dependent. The present model is so general that it is capable of solving various geometries from single curve to doubly curved panel, including the flat panel.

This study aims to investigate the flow and heat transfer of a hybrid nanofluid through an exponentially stretching/shrinking sheet along with mixed convection and Joule heating. The nanoparticles alumina (Al₂O₃) and copper (Cu) are suspended into a base fluid (water) to form a new kind of hybrid nanofluid (Al₂O₃-Cu/water). Also, the effects of constant mixed convection parameter and Joule heating are considered.

The governing partial differential equations are transformed into ordinary differential equations (ODEs) using appropriate similarity transformations. The transformed nonlinear ODEs are solves using the bvp4c solver available in MATLAB software. A comparison of the present results shows a good agreement with the published results.

Dual solutions for hybrid nanofluid flow obtained for a specific range of the stretching/shrinking parameter values. The values of the skin friction coefficient increases but the local Nusselt number decreases for the first solution with the increasing of the magnetic parameter. Enhancing copper volume fraction and Eckert number reduces the surface temperature, which intimates the decrement of heat transfer rate for the first and second solutions for the stretching/shrinking sheet. In detail, the first solution results show that when the Eckert number increases as 0.1, 0.4 and 0.7 at λ = 1.5, the temperature variations reduced to 10.686840, 10.671419 and 10.655996. While in the second solution, keeping the same parameters temperature variation reduced to 9.750777, 9.557349 and 9.364489, respectively. On the other hand, the results indicate that the skin friction coefficient increases with copper volume fraction. This study shows that the thermal boundary layer thickness rises due to the rise in the solid volume fraction. It is also observed that the magnetic parameter, copper volume fraction and Eckert number widen the range of the stretching/shrinking parameter for which the solution exists.

In practice, the investigation on the flow and heat transfer of a hybrid nanofluid past an exponentially stretching/shrinking sheet with mixed convection and Joule heating is crucial and useful. The problems related to hybrid nanofluid have numerous real-life and industrial applications, such as microelectronics, manufacturing, naval structures, nuclear system cooling, biomedical and drug reduction.

In specific, this study focuses on increasing thermal conductivity using a hybrid nanofluid mathematical model. The novelty of this study is the use of natural mixed convection and Joule heating in a hybrid nanofluid. This paper can obtain dual solutions. The authors declare that this study is new, and there is no previous published work similar to the present study.