Conventional Fluid Research Articles

Investigation on the pressure and flow characteristics for a high-speed bullet in high-altitude flight

The pressure analysis and flow characteristics during the flight of a high-speed bullet are significant for aerodynamic performance, flight trajectory control, safety and reliability, performance optimization, guidance and navigation. To accurately monitor the pressure variation for a high-speed bullet in the high-altitude flight, a novel local fluid domain method is introduced in current study. This method overcomes the limitations of conventional global fluid domain simulation methods, which often suffer from poor convergence and stability issues. On the basis, the force analysis is conducted and the mathematical model for the theoretical trajectory is established, which is applied to simulate the flight trajectory and construct fluid domain for the high-speed bullet. The findings reveal that monitoring points within the bullet hole are influenced by both cavity flow and the collision of forward airflows during the high-altitude flight. Furthermore, it is observed that the absolute total pressure and reference pressure at these monitoring points within the bullet hole are influenced by altitude variations. Subsequently, the factors affecting the absolute total pressure within the hole are explored, including the hole depth, the hole diameter, the hole position, and the bullet orientation. The results indicate that modifying the bullet structure to incorporate 45° angled hole, as opposed to standard holes, can lead to a 13.6% reduction in absolute total pressure variation. Additionally, mitigating the interaction between the external and internal fluids emerges as a critical factor in reducing absolute total pressure within the hole. This research not only presents a fresh perspective for pressure monitoring within the bullet hole, but also establishes a theoretical foundation for the precise guidance of high-altitude bullets.

Predictive modelling of thermal conductivity in single-material nanofluids: a novel approach

BackgroundThis research introduces a novel approach for modelling single-material nanofluids, considering the constituents and characteristics of the fluids under investigation. The primary focus of this study was to develop models for predicting the thermal conductivity of nanofluids using a range of machine learning algorithms, including ensembles, trees, neural networks, linear regression, Gaussian process regressors, and support vector machines.The main body of the abstractTo identify the most relevant features for accurate thermal conductivity prediction, the study compared the performance of established feature selection algorithms, such as minimum redundancy maximum relevance, Ftest, and RReliefF, a newly proposed feature selection algorithm. The novel algorithm eliminated features lacking direct implications for fluid thermal conductivity. The selected features included temperature as a thermal property of the fluid itself, multiphase features such as volume fraction and particle size, and material features including nanoparticle material and base fluid material, which could be fixed based on any two intensive properties. Statistical methods were employed to select the features accordingly.ResultsThe results demonstrated that the novel feature selection algorithm outperformed the established approaches in predicting the thermal conductivity of nanofluids. The models were evaluated using fivefold cross-validation, and the best model was the model based on the proposed feature selection algorithm that exhibited a root-mean-squared error of validation of 1.83 and an R-squared value of 0.94 on validation set. The model achieved a root-mean-squared error of 1.46 and an R-squared value of 0.97 for the test set.ConclusionsThe developed predictive model holds practical significance by enabling nanofluids' numerical study and optimisation before their creation. This model facilitates the customisation of conventional fluids to attain desired fluid properties, particularly their thermal properties. Additionally, the model permits the exploration of numerous nanofluid variations based on permutations of their features. Consequently, this research contributes valuable insights to the design and optimisation of nanofluid systems, advancing our understanding and application of thermal conductivity in nanofluids and introducing a novel and methodological approach for feature selection in machine learning.

Artificial neural network modeling of mixed convection viscoelastic hybrid nanofluid across a circular cylinder with radiation effect: Case study

As a result of its use in the manufacturing and construction industries, research on the flow of nanofluid is rather well-known among academics and professionals in related fields. It is helpful for electrical equipment to utilize it for cooling reasons, which has shown promising results in terms of reducing energy use. As a result, the primary objective of this research is to inspect the impacts that radiation has on the mixed convection of Walters'-B hybridity nanofluid flow of stagnant point in a horizontal circular cylinder under the circumstances of a constant heat flux. It is considered a conventional fluid despite the presence of copper (Cu) and alumina (Al2O3) nanoparticles in the water (H2O) hybridity nanofluid. To make the solution to the resulting controlling system of equations more straightforward, the numerical approach of a neural network with a back-propagation algorithm (NN-BPA) is used. It follows by clarifying how various physical characteristics, such as blended convection, thermal radiation, and stagnant movement, affect temperature, skin friction, thermal transfer, velocity, and graphical profiles of those variables. The LMNN-BPA has the quickest processing algorithm and performs well in general, corresponding to the thorough analysis. Additionally, the mixed convective and viscoelastic properties exhibit both rising and dropping developments regarding skin friction and heat transmission.

Exploring the effect of raw material properties on continuous twin-screw wet granulation manufacturability

Twin-screw wet granulation (TSWG) stands out as a promising continuous alternative to conventional batch fluid bed- and high shear wet granulation techniques. Despite its potential, the impact of raw material properties on TSWG processability remains inadequately explored. Furthermore, the absence of supportive models for TSWG process development with new active pharmaceutical ingredients (APIs) adds to the challenge. This study tackles these gaps by introducing four partial least squares (PLS) models that approximate both the applicable liquid-to-solid (L/S) ratio range and resulting granule attributes (i.e., granule size and friability) based on initial material properties. The first two PLS models link the lowest and highest applicable L/S ratio for TSWG, respectively, with the formulation blend properties. The third and fourth PLS models predict the granule size and friability, respectively, from the starting API properties and applied L/S ratio for twin-screw wet granulation. By analysing the developed PLS models, water-related material properties (e.g., solubility, wettability, dissolution rate), as well as density and flow-related properties (e.g., flow function coefficient), were found to be impacting the TSWG processability. In addition, the applicability of the developed PLS models was evaluated by using them to propose suitable L/S ratio ranges (i.e., resulting in granules with the desired properties) for three new APIs and related formulations followed by an experimental validation thereof. Overall, this study helped to better understand the effect of raw material properties upon TSWG processability. Moreover, the developed PLS models can be used to propose suitable TSWG process settings for new APIs and hence reduce the experimental effort during process development.

Prediction of Viscosity of Cobalt Ferrite/SAE50 Engine Oil based Nanofluids using well Trained Artificial Neutral Network (ANN) and Response Surface Methodology (RSM)

Heat transmission by ordinary fluids such as pure water, oil, and ethylene glycol is inefficient due to their low viscosity. To boost the efficiency of conventional fluids, very small percent of nanoparticles are added to the base fluids to prepare nanofluid. The impact of changing in viscosity can be used to investigate the rheological properties of nanofluids. In this paper, (CoFe2O4)/engine oil based nanofluids were prepared using two steps standard methodology. In first step, CoFe2O4 (CF) were synthesized using the sol-gel wet chemical process. The crystalline structure and morphology were confirmed using X-Ray diffraction analysis (XRD) and scanning electron microscopy (SEM), respectively. In second step, the standard procedure was adapted by taking several solid volume fractions of CF as Ø = 0, 0.25, 0.50, 0.75, and 1.0 %. Such percent of concentrations were dispersed in appropriate volume of engine oil using the ultrasonication for 5 h. After date, the viscosity of prepared five different nanofluids were determined at temperatures ranging from 40 to 80 °C. According to the findings, the viscosity of nanofluids (µnf) decreased as temperature increased while increased when the volume percentage of nanofluids Ø raised. Furthermore, total 25 experimental observations were considered to predict viscosity using an artificial neural network (ANN) and response surface methodology (RSM). The algorithm for building the ideal ANN architecture has been recommended in order to predict the fluid velocity of the CF/SAE-50 oil based nanofluid using MATLAB software. In order to determine the correctness of the predicted model, the mean square error (MSE) was calculated 0.0136.

Numerical thermal study of ternary nanofluid influenced by thermal radiation towards convectively heated sinusoidal cylinder

ApplicationsThe heat transfer remains a huge problem for industrialists and engineers because many production processes required considerable amount of heat to finish the process successfully. Although, conventional fluids have large scale industrial applications but unable to provide huge amount of heat transfer. Therefore, the study is organized to propose a new ternary heat transfer model using different physical constraints. The key applications area of nanofluid heat transfer are chemical, applied thermal and food processing engineering. Purposeand Methodology: The key purpose of this research is introduce a new ternary nanofluid model using the impressive effects of thermal radiations, surface convection and saddle/nodal points. The results simulated via RKF-45 and discussed in detail. Core findingsThe strength of Al2O3 nanoparticles form 1%–7% (keeping fixed CuO and Cu as 4% and 6%) and s1 = −0.2,-0.4,-0.6,-0.8 controlled the fluid movement while s1 = 0.2,0.4,0.6,0.8 boosted the velocity. Increasing the convection process Bi = 0.1,0.2,0.3,0.4 increased the temperature significantly. Further, shear drag is maximum for ternary nanofluid and thermal radiations Rd = 0.1,0.2,0.3,0.4 enhances the heat transfer rate.

A Review Paper on Properties and Applications of Nanofluids

A nanofluid is a liquid that contains nanometer-sized particles. Nanofluids are obtained by dispersing nanometer-sized particles in conventional base fluids such as water, oil, ethylene glycol, etc. Nanoparticles of materials such as metallic oxides (Al2O3, CuO), nitride ceramics (AlN, SiN), carbide ceramics (SiC, TiC), metals (Cu, Ag, Au), semiconductors (TiO2, SiC), single, double or multi-walled carbon nanotubes, alloyed nanoparticles (Al70, Cu30), etc., were used to prepare the nanofluids. This paper presents a procedure for preparing Nanofluids, the properties of Nanofluids, and their applications in various fields, including energy, mechanics, and biomedicine. Then it defines the parameter that challenges the use of Nanofluids in different applications and finally suggests directions for future research on Nanofluids. The thermal conductivity of the Nanofluids is improved at a very low (< 0.1%) percentage of suspended particles. Nowadays, Nanofluids are used efficiently in non-traditional energy resources in absorbing solar energy to increase the temperature.

Performances Investigation of the Eco-friendly Refrigerant R13I1 used as Working Fluid in the Ejector-Expansion Refrigeration Cycle

Knowing that from 2030 refrigerants used in refrigerating engineering should have a global warming potential (GWP) of less than 150. Searching for eco-friendly refrigerants with good performance and minimal environmental impact to substitute conventional working fluids such as R134a (GWP=1430) represents a great challenge for researchers.&#x0D; The present research aims to investigate and compare the performances of the eco-friendly refrigerant R13I1 (Zero GWP) used as a possible new working fluid in the ejector-expansion refrigeration cycle (EERC) with the commonly used R134a which has good performances but a high GWP. To reach this objective, a numerical program was developed using MATLAB software to evaluate the coefficient of performance (COP), the entrainment ratio (µ), the exergy destruction and the exergy efficiency for both refrigerants. Furthermore, the effect of the diffuser efficiency of the ejector on the COP and the compressor work was explored. Furthermore, the effect of the diffuser efficiency of the ejector on the COP, and the compressor work were explored. The simulation was realized for Tc selected between 30 and 55 °C and Te ranging between -10 and 10 °C. Results proved that the use of R13I1 as a working fluid in the EERC system exhibited a higher COP, µ, and exergy efficiency, as well as lower exergy destruction compared with R134a under the same operating temperatures. On another hand, the energetic analysis revealed that as Tc increases the COP and µ decrease. However, as Te varies from -10 and 10 °C, the COP and µ increase. Regarding exergy analysis, it should be noted that both exergy destruction and exergy efficiency are sensitively influenced by Tc more than Te. Overall, the study confirms that R13I1 could be a suitable substitute for the phase-out R134a in terms of performance and environmental protection.

Synthesis and Characterization of BaO-Enhanced Therm500 Nanofluids

In this study, we enhance the thermal conductivity of the conventional heat transfer fluid Therm500 by incorporating BaO nanoparticles. BaO:Therm500 nanofluids are synthesized and characterized at various concentrations (ranging from 0.001 to 0.006 g) and temperatures (300 K, 303 K, 313 K, and 323 K). The investigation includes the use of FT-IR spectroscopy to analyze the interaction between BaO nanoparticles and Therm500. Our findings indicate that there is no significant particle-fluid interaction. The enhanced thermal conductivity observed in BaO:Therm500 nanofluids is attributed to multiple factors. As the temperature increases, the viscosity of the nanofluid decreases, resulting in increased Brownian motion of nanoparticles and convective-like effects, ultimately leading to improved thermal conductivity. Additionally, we report the acoustic properties of BaO-Enhanced Therm500 nanofluids at the same four temperatures (300 K, 303 K, 313 K, and 323 K). Density, refractive index, and ultrasonic velocity measurements are performed for six different molar concentrations of BaO nanofluids (0.001 g, 0.002 g, 0.003 g, 0.004 g, 0.005 g, and 0.006 g). Subsequently, various acoustical parameters, such as adiabatic compressibility (β), intermolecular free length (Lf ), specific acoustic impedance (Z), Rao’s constant (R), molar compressibility (W), viscous relaxation time (τ), free volume (Vf ), Gibbs free energy (ΔG), and internal pressure (πi), are calculated. These acoustical characteristics are utilized to investigate molecular interactions within the nanofluid system. The study reveals a non-linear relationship between ultrasonic velocity and particle concentration, which is attributed to weak particle-fluid interactions. These findings provide valuable insights into the preparation and characterization of BaO-enhanced Therm500 nanofluids and their potential applications in heat transfer systems.

Numerical investigation of magnetized nanofluid flow with thermal radiation and homogeneous/heterogeneous reactions over a vertical cylinder

Nanofluid flow has gained attention due to its promising applications in numerous industries. Nanofluids exhibit a significant advantage over conventional fluids due to their superior heat transfer capability, attributed to the presence of nanoparticles that enhance thermal conductivity, resulting in improved heat dissipation and efficiency. Current research aims to numerically investigate the impact of homogeneity and heterogeneity on the mixed convection flow of incompressible viscous nanofluids through a vertically permeable cylinder under suction/injection circumstances. The study also considers thermal radiation and heat source/sink phenomena. Ethylene glycol is utilized as base fluid, while nanoparticles include silicon carbide SiC and Titanium dioxide TiO2. The mathematical flow model, based on nonlinear partial differential equations (PDEs), is converted into ordinary differential equations (ODEs) by using suitable similarity transformations that pronounced nonlinear system of ODEs. To deal with this nonlinear system, the bvp4c and shooting methods are used in the commercial software MATLAB to solve these ODEs numerically. The impacts of flow parameters on various quantities of interest are elaborated graphically. From obtained results it is analyzed that velocity field boosts up versus higher values of nanoaprticle volume fraction. The velocity field is decreases with increasing the amount of magnetic field. An increase in the thermal field is observe with a rise in the thermal radiation parameter. The good agreement between current results and published work is noted.

Synthesis of nanofluids preparation – A review

Over two decades, the scientists and engineers having higher prospects on the rapid development of nanotechnology. The size of suspended nanoparticles in the nanofluids were below 100 nm in heat transfer offers substantial advantages compared to the conventional fluids in the heat transfer applications.Thermal properties of host fluids improves with the stably suspended and uniformly dispersed nanoparticles in the base fluids. This work is mainly focused on the state-of-the-art advances for nanofluids preperation. For preperating highly conductive nanofluids with stability nature, one-step and two-step methods are widely used.

A Study on the Oil-Bearing Stability of Salt-Resistant Foam and an Explanation of the Viscoelastic Phenomenon

Foam is a medium-stable system composed of gas and liquid phases, which has the advantages of low density at the gas phase and high viscosity at the liquid phase, and has a wide application in oil and gas field development and mineral flotation, but its special medium-stable system also brings many problems in industry applications. Scientists have carried out extensive analyses and research on the foam stability and bubble-bursting mechanism, which initially clarified the rules of bubble breakage caused by environmental factors such as temperature and pressure, but the mechanism of bubble bursting under the action of internal factors such as liquid mineralization and oil concentration of the films is still not clearly defined. In this paper, we propose a compound salt-resistant foaming agent, investigated the influence of the aggregation and adsorption behavior of oil droplets on the liquid films and boundaries, and established a relevant aggregation and adsorption model with the population balance equation. We put forward a liquid film drainage mechanism based on the distribution, aggregation, and transport of oil droplets in the liquid films, so as to explain the changes in foam stability under the action of oil droplets. On the other hand, the viscoelastic analysis of foam fluid is performed with a rheometer, and the results show that in comparison with conventional power-law fluid, foam fluid has a complex rheological behavior for low shear thickening, but high shear thinning.

Application of fluid modulus inversion to complex lithology reservoirs in deep-water areas

It has been a challenge to distinguish between seismic anomalies caused by complex lithology and hydrocarbon reservoirs using conventional fluid identification techniques, leading to difficulties in accurately predicting hydrocarbon-bearing properties and determining oil-water contacts in reservoirs. In this study, we built a petrophysical model tailored to the deep-water area of the Baiyun Sag in the eastern South China Sea based on seismic data and explored the feasibility of the tri-parameter direct inversion method in the fluid identification of complex lithology reservoirs, offering a more precise alternative to conventional techniques. Our research found that the fluid modulus can successfully eliminate seismic amplitude anomalies caused by lithological variations. Furthermore, the seismic data-based direct inversion for fluid modulus can remove the cumulative errors caused by indirect inversion and the influence of porosity. We discovered that traditional methods using seismic amplitude anomalies were ineffective in detecting fluids, determining gas-water contacts, or delineating high-quality reservoirs. However, the fluid factor Kf, derived from solid-liquid decoupling, proved to be sensitive to the identification of hydrocarbon-bearing properties, distinguishing between high-quality and poor-quality gas zones. Our findings confirm the value of the fluid modulus in fluid identification and demonstrate that the tri-parameter direct inversion method can significantly enhance hydrocarbon exploration in deep-water areas, reducing associated risks.

Modeling displacement flow inside a full-length casing string for well cementing

While computer modeling of annular displacement efficiency is widely applied in cementing engineering, modeling the displacement flow inside a casing or drill string for cementing operations has received less attention. Although predicting displacement efficiency inside a full-length pipe is desired by cementing engineers, the attempt of developing a model with both efficiency and accuracy faces challenges. Access to computer simulators for this purpose is limited. Compared with annular flow, the displacement flow inside pipe, although within a simpler geometry and without eccentricity effect, is not simpler in physics, modelling strategy and predictability, because a variety of flow patterns and flow instabilities can develop to create complicated fluid interfaces. In this paper, we present an integrated numerical model developed to simulate displacement flows inside a full-length pipe, which connects an existing annulus model to enable complete displacement simulations of cementing jobs. The model uses three-dimensional grid to solve fluid concentrations with degrees of mixing, and incorporates flow instability detection and flow regime determination. Applied in cementing, the model accounts for effects of pumping rate, well inclination, pipe rotation, fluid densities, rheological parameters and more. This computationally efficient model does not rely on high-resolution mesh as often required by conventional Computational Fluid Dynamics models, thus it is suitable to be implemented in a cementing software for daily use by well cementing engineers. The methodology of the model is discussed in detail in this paper. To validate the model, we examine simulation results against experimental results obtained in our laboratory tests and CFD simulations; acceptable agreement is found under different testing conditions. We also presented two case studies of real cementing jobs with cement evaluation logs compared to simulation results, showing that the model can predict consistent displacement efficiency results.

Eco-friendly drilling fluid: A study on the use of broad bean peels as a natural additive

Drilling fluid is an essential part of the oil and gas drilling process because it provides the drill bit hydraulic pressure, cools and lubricates the drill, and transports the drilled cuttings to the surface. However, using conventional drilling fluids can have a negative influence on the environment as well as high costs. In order to overcome these issues, experts have recently looked into the use of sustainable and natural additives in drilling fluids. The possibility of using broad bean peels, a frequently encountered agricultural waste, as a natural component in drilling fluid is examined in this study. Testing methods used to assess the effectiveness of broad bean peels as a rheological modifier in drilling fluid included rheological measures, filtration tests, and infrared spectroscopic studies. The results show there is a noticeable trend of increasing plastic viscosity from 7 to 14 and yield point from 3 to 13 as the concentration increased from zero to 8 g. The 10-s gel strength of the drilling fluid also increased from 4 to 23, and the 10-min gel strength increased from 5 to 30 in the same concentration range. Filtration tests showed that the addition of broad bean peels at a concentration of 2% by weight reduced the filtrate loss by 12%, indicating reduced in filter cake thickness. According to the findings, broad bean peels can improve the rheological characteristics of drilling fluid, decrease fluid loss, and provide significant insight into the chemical make-up of the peels that can be used to maximize their effectiveness as drilling fluid additives. According to these findings, broad bean peels might be a practical and long-term replacement for conventional drilling fluid additives, resulting in drilling operations that are more cost- and environmentally-conscious.

Mass Transfer-Promoted Fe2+/Fe3+ Circulation Steered by 3D Flow-Through Co-Catalyst System Toward Sustainable Advanced Oxidation Processes

Realizing fast and continuous generation of reactive oxygen species (ROSs) via iron-based advanced oxidation processes (AOPs) is significant in the environmental and biological fields. However, current AOPs assisted by co-catalysts still suffer from the poor mass/electron transfer and non-durable promotion effect, giving rise to the sluggish Fe2+/Fe3+ cycle and low dynamic concentration of Fe2+ for ROS production. Herein, we present a three-dimensional (3D) macroscale co-catalyst functionalized with molybdenum disulfide (MoS2) to achieve ultra-efficient Fe2+ regeneration (equilibrium Fe2+ ratio of 82.4%) and remarkable stability (more than 20 cycles) via a circulating flow-through process. Unlike the conventional batch-type reactor, experiments and computational fluid dynamics simulations demonstrate that the optimal utilization of the 3D active area under the flow-through mode, initiated by the convection-enhanced mass/charge transfer for Fe2+ reduction and then strengthened by MoS2-induced flow rotation for sufficient reactant mixing, is crucial for oxidant activation and subsequent ROS generation. Strikingly, the flow-through co-catalytic system with superwetting capabilities can even tackle the intricate oily wastewater stabilized by different surfactants without the loss of pollutant degradation efficiency. Our findings highlight an innovative co-catalyst system design to expand the applicability of AOPs based technology, especially in large-scale complex wastewater treatment.

Rock-physics model of hydrate reservoirs considering fluid inhomogeneous mixing, the temperature dependence of hydrate elastic modulus, and simplified pore structure parameters

Rock-physics modeling of hydrate reservoirs is an efficacious solution for assessing the macroscopic elastic responses of rocks induced by microphysical parameters, pore structure, and fluid properties. Although many applicable rock-physics models have been proposed successively for different research objectives, several issues still need attention. Firstly, the previous studies have mainly focused on the effects of hydrate distribution morphology and pore structure, ignoring the mixing characteristics of different components in the pore fluid. Secondly, since the elastic modulus of hydrates differs greatly from that of conventional fluids, the reasonable setting of its elastic parameters will significantly affect the estimation results of the model. Additionally, too many parameters describing the pore structure will bring great uncertainty to the calculation results, while how to further consider the unconsolidated characteristics of the hydrate sediments in the modeling needs to be further investigated. To address the above problems, CT images of cores were used to elucidate the mixing relationship of hydrate, water, and gas, and the calculation of the equivalent fluid elastic modulus was proposed. The temperature dependence of the hydrate elastic modulus is obtained from experimental data and the elastic parameters are assigned by temperature in the modeling process. On this basis, the descriptive parameters of the pore structure are simplified by using the equivalent shape factor, and the unconsolidated characteristic of the sediments is described by introducing the consolidation parameter. In this study, we proposed a new modeling process for hydrate reservoirs and elaborated the rationality and necessity of the modeling idea in the numerical analysis, which finally achieved satisfactory results in the field data collected at the South China Sea.

Dynamic Characteristics of MR Fluid Short Squeeze Film Damper in Terms of Reynolds Number

Magnetorheological (MR) fluids are suspensions of fine micron-sized particles suspended in an appropriate carrier medium. Their rheological properties can be controlled by the application of an appropriate magnetic field and can be used in a variety of applications where damping and stiffness characteristics need to be controlled at a particular excitation frequency, based on the requirements. This cannot be accomplished with conventional fluids and thus MR fluids find application in squeeze film dampers of aircraft jet engines to provide variable damping in accordance with the magnetic field, at a particular excitation frequency. Limited information is available on the stiffness and damping characteristics of magnetorheological fluid squeeze film dampers in the literature. This paper provides information on the stiffness and damping characteristics of MR fluids used as external damping medium in Squeeze film Dampers in terms of the Reynolds number of the squeeze film. The paper calibrates the stiffness and damping characteristics of particular magnetorheological fluid squeeze film damper theoretically in terms of Reynolds number of the squeeze film for two clearance and L/D ratios operating at low eccentricity ratios, using a constant field viscosity model. The stiffness and damping characteristics are found to decrease with the increase in Reynolds number. The Reynolds number of the squeeze film is very low, highlighting the fact that the flow in the film has ceased and has solidified in accordance with the literature. The dynamic coefficients are presented in the form of empirical equations based on the theoretical investigations for different clearance, L/D ratio and eccentricity ratio, in terms of Reynolds number of the damper and enables its easy evaluation for a particular damper configuration by a mere knowledge of the Reynolds number of the squeeze film. The results assist the designer in obtaining the stiffness and damping characteristics of the squeeze film damper, based on the Reynolds number. Alternatively, the stiffness and damping characteristics of the squeeze film damper are calibrated in terms of Reynolds number for particular damper configurations. However, the research focuses on the stiffness and damping coefficients for a limited number of damper configurations under a constant excitation frequency whilst a large number of clearances, L/D ratios and excitation frequencies have not been taken into account .This research is thus intended only to showcase the method of approach by selecting finite number of damper configurations. Future work should be focused towards investigations that present the empirical equations for the entire range of clearance, L/D ratio and eccentricity ratio.

Lattice Boltzmann simulation of natural convection of ethylene glycol-alumina nanofluid in a C-shaped enclosure with MFD viscosity through a parallel computing platform and quantitative parametric assessment

There has been a strong interest to design and optimise thermally efficient heating and cooling equipment. The conventional fluids such as oil and water have limited thermal efficiency. Therefore, researchers have been seeking alternatives to the conventional fluids to improve the efficacy of heat exchanging and electronic cooling devices and nanofluid has been identified as a great option in this regard. Although nanofluid is a great alternative, certain specifications, geometries, and pertinent parameters need to be thoroughly investigated for a comprehensive understanding with the aid of robust computational technique. The aim of this study was to investigate the multiple-relaxation-time (MRT) lattice Boltzmann method (LBM) to numerically analyse the effects of magnetic field dependent (MFD) viscosity on the natural convection of ethylene glycol (C2H6O2)-alumina (Al2O3) nanofluid in a side heated two-dimensional C-shaped enclosure using graphics processing unit (GPU) by a computing unified device architecture (CUDA) C parallel computing platform. Numerical simulations were performed at multifarious Rayleigh numbers, Hartmann numbers, and the different magnetic field inclination angles to study the heat transfer and various flow patterns under magnetic field-dependent (MFD) viscosity, solutions were presented by varying volume fraction of nanoparticles, Rayleigh numbers, viscous parameters, magnetic inclination angles, and Hartman numbers on streamlines, isotherms, local and average Nusselt number and temperature. Further correlation developments were conducted through Levenberg-Marquardt data-driven algorithm to investigate the influence of all the parameters on average Nusselt numbers, entropy generation, and fluid irreversibility parameter. The findings demonstrated that as the Rayleigh numbers augmented, the average Nusselt number increased significantly due to the influence of buoyancy, whereas under the influence of Hartmann numbers, average Nusselt numbers decreased due to the dominance of magnetic field strength and Lorentz force. However, the heat transfer continued to improve if the concentration of the nanoparticles increased, thus showcasing the importance of hybrid nanofluid. In addition, the entropy generation impact across the cavity for the ethylene glycol-alumina nanofluid was greatly enhanced by a stronger buoyancy influence.

Development of a Multiwalled Carbon Nanotube Voltage Sensor Using Copper Oxide Nanofluids

Carbon Nanotubes (CNT) are allotropes of carbon having superior mechanical, electronic, physical, and optical properties. When a fluid is passed through the nanotubes, the fluid exerts a mechanical force on the walls of the CNT due to which a strain is induced on the surface of the carbon nanotubes creating a net charge at the center of the strained hexagon. This induced polarity produces a voltage across the nanotubes. In this project, nanofluids (cuprous oxide in ethylene glycol) in addition to conventional fluids were passed through multi-walled carbon nanotubes, and a voltage was observed (upto 4.1 mV in the case of nanofluids) after the capillary rise of the flowing fluid in the nanotube sensor. This was in agreement with previously conducted studies on the piezoelectric effect due to the flow of conventional fluids on single-walled carbon nanotubes. The voltage generated across the multi-walled carbon nanotubes (MWCNTs) for the different fluid systems was compared and characterization was done with respect to the fluid system. An attempt was made to present voltage generated as a function of the fluid and flow properties. The paper aims to highlight the possible use of MWCNTs in sensor-based technology and energy conversion devices.