Numerical Simulation of MHD Fluid Flow inside Constricted Channels using Lattice Boltzmann Method

In this study, the electrically conducting fluid flow inside a channel with local symmetric constrictions, in the presence of a uniform transverse magnetic field is investigated using Lattice Boltzmann Method (LBM). To simulate Magnetohydrodynamics (MHD) flow, the extended model of D2Q9 for MHD has been used. In this model, the magnetic induction equation is solved in a similar manner to hydrodynamic flow field which is easy for programming. This extended model has a capability of simultaneously solving both magnetic and hydrodynamic fields; so that, it is possible to simulate MHD flow for various magnetic Reynolds number (Rem). Moreover, the effects of Rem on the flow characteristics are investigated. It is observed that, an increase in Rem, while keeping the Hartman number (Ha) constant, can control the separation zone; furthermore, comparing to increasing Ha, it doesn't result in a significant pressure drop along the channel

Author Correction: Metabolomic epidemiology offers insights into disease aetiology

Correction to "Metabolomic epidemiology offers insights into disease aetiology

Forced convection around horizontal tubes bundles of a heat exchanger using a two-phase mixture model: Effects of nanofluid and tubes Configuration

In this paper, numerical simulation of laminar flow and heat transfer of nanofluid on a group of heat exchanger tubes is described. For better prediction of the behavior of the nanofluid flow on the tube arrays, two-phase mixture model was used. To achieve this aim, heat transfer and laminar flow of two-phase nanofluid as cooling fluid at volume fraction of 0, 2, 4, and 6% solid nanoparticles of silver and Reynolds numbers of 100 to1800 were investigated for different Configurations of tube arrays. The results indicated when the nanofluid collides with the tube arrays, the growth of heat boundary layer and gradients increase. The increase in the growth of boundary layer in the area behind the tubes was very remarkable, such that at the Reynolds number of 100, due to diffusion of the effect of wall temperature in the cooling fluid close to the wall, it had a considerable growth. Further, from the second row onwards, the slope of pressure drop coefficient diagrams was descending. Among the different Configuration s of tubes and across all the investigated Reynolds numbers, square Configuration had the maximum pressure drop coefficient as well as the highest extent of fluid momentum depreciatio

Metabolomic epidemiology offers insights into disease aetiology

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer’s disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression

Effects of graphene oxide‑silicon oxide hybrid nanomaterials on rheological behavior of water at various time durations and temperatures: Synthesis, preparation and stability

The present empirical study investigates the synthesis of graphene oxide nanoparticles, preparation of water/graphene oxide‑silicon oxide hybrid nanofluid, and parameters affecting viscosity of the nanofluid. Graphene oxide nanoparticles are synthesized using the modified Hummer's method. Surface structure and atomic structure of the nanoparticles were studied using SEM and XRD tests. The nanofluid was then prepared using the two step method. DLS tests with various patterns were used, in addition to sedimentation photograph capturing method, to measure stability of the nanofluid. Results suggested that the nanofluid has a fairly suitable nanostructure. Viscosity of the nanofluid was measured and studied using Brookfield DV2EXTRA-Pro Viscometer, in the temperature range of 20–60 °C with volume concentrations of 0, 0.5, 0.1, 0.2, 0.4, 0.6, 0.8, and 1%. Furthermore, effects of parameters such as shear rate, and period of applying constant shear rate on viscosity of the nanofluid were investigated. The test results showed that viscosity behavior of the nanofluid is independent of the shear rate and time of shearing. Numerical viscosity measurement results show that viscosity of the nanofluid with volume concentration of φ = 1%, in temperature of 20 °C, increased considerably to μ = 2.42 mPa·s. Viscosity changes ratio increases intensively in higher concentrations. Comparing empirical results of water/graphene oxide nanofluid viscosity to results of the present study shows that, due to the modification of surface structure in nanoparticles, the viscosity values have improved considerably. An empirical equation is provided to measure the viscosity of the nanofluid using this data, which can be used to calculate viscosity of the base fluid under effect of temperature, and viscosity of the nanofluid under effect of temperature and volume concentration variables

A new experimental correlation for non-Newtonian behavior of COOH-DWCNTs/antifreeze nanofluid

In this paper, the rheological behavior of nano-antifreeze consisting of 50%vol. water, 50%vol. ethylene glycol and different quantities of functionalized double walled carbon nanotubes has been investigated experimentally. Initially, nano-antifreeze samples were prepared with solid volume fractions of 0.05, 0.1, 0.2, 0.4, 0.6, 0.8 and 1% using two-step method. Then, the dynamic viscosity of the nano-antifreeze samples was measured at different shear rates and temperatures. At this stage, the results showed that base fluid had the Newtonian behavior, while the behavior of all nano-antifreeze samples was non-Newtonian. Since the behavior of the samples was similar to power law model, it was attempted to find the constants of this model including consistency index and power law index. Therefore, using the measured viscosity and shear rates, consistency index and power law index were obtained by curve-fitting method. The obtained values showed that consistency index amplified with increasing volume fraction, while reduced with enhancing temperature. Besides, the obtained values for power law index were less than 1 for all samples which means shear thinning behavior. Lastly, new correlations were suggested to estimate the consistency index and power law index using curve-fitting